{
  "data": {
    "a": {
      "slug": "eden-ai",
      "name": "Eden AI",
      "vendor": "Eden AI SAS",
      "vendorUrl": "https://www.edenai.co",
      "kind": "router",
      "category": "inference",
      "summary": "Eden AI is a French AI gateway with one OpenAI-compatible API key for about 1,000 chat and expert models from 80 or more providers, including OCR, speech, translation and image analysis, with an EU-only endpoint and a hosted MCP server.",
      "url": "https://www.anchorterminal.com/tools/eden-ai",
      "markdownUrl": "https://www.anchorterminal.com/tools/eden-ai.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/eden-ai.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/eden-ai.json",
      "dns": "eden-ai.grade.anchorterminal.com",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://mcp.edenai.run/mcp",
      "packages": [],
      "auth": "api-key",
      "authNotes": "Bearer key created in the dashboard at app.edenai.run after a browser signup. Keys carry budgets, expiry and attribution, can be managed through a key API, and can be limited to chosen models by deny-by-default guardrails. The MCP server takes the same key in the Authorization header.",
      "pricing": "usage",
      "pricingNotes": "Provider list prices with no markup plus a 5.5% platform fee applied when buying credits. Prepaid credits through Stripe by card, PayPal or bank transfer, with optional auto-refill. Some models are billed $0 for tests. The Advanced plan is by quote.",
      "priceSummary": "5.5% fee",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in llms.txt, the OpenAPI spec, the pricing pages or the agent catalogue (checked 2026-11-06). Credits are bought through Stripe.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://www.edenai.co/docs",
      "llmsTxt": "https://www.edenai.co/llms.txt",
      "openapi": "https://api.edenai.run/v3/docs/openapi.json",
      "capabilities": [
        "inference.router",
        "inference.llm",
        "embed.text",
        "translate.text",
        "translate.documents",
        "docs.ocr",
        "speech.stt",
        "speech.tts",
        "image.generate",
        "guard.moderation"
      ],
      "tags": [
        "hosted",
        "router",
        "openai-compatible",
        "usage-priced",
        "prepaid",
        "mcp",
        "remote-mcp",
        "api-key",
        "llms-txt",
        "openapi",
        "eu",
        "eu-region",
        "soc2",
        "iso27001",
        "batch",
        "closed-source"
      ],
      "lastRelease": "2026-11-05",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.9,
        "grade": "C",
        "agentReady": false,
        "rank": 675,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 22,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 75,
          "maintenance": 58,
          "payments": 30,
          "reliability": 33,
          "schema": 81,
          "security": 82,
          "transparency": 55
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.",
        "bestFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.",
        "strengths": [
          "OpenAI-compatible v3 API with an OpenAPI 3.1 spec and a keyless model catalogue with prices and regions",
          "EU endpoint that refuses models not cleared for European processing with HTTP 451",
          "Content isn't stored or used for training by default, with opt-in logs and enforceable Zero Data Retention",
          "Per-key budgets, expiry and deny-by-default guardrails, plus a key management API",
          "Hosted MCP server exposing OCR, speech, translation, web search and other expert models as tools"
        ],
        "weaknesses": [
          "No public status page, incident history or SLA found",
          "The rate-limits page says 10 requests a second and the plans page says 7, raisable to 15",
          "No public changelog or deprecation policy",
          "The OpenAPI spec documents few error responses",
          "Credits are prepaid through Stripe with a 5.5% platform fee on every purchase"
        ],
        "agentNotes": [
          "Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them",
          "Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed",
          "Set max_tokens to 500 or more for reasoning models, or the answer can come back empty",
          "Pass a fallbacks list so a provider 429 or error retries inside one request",
          "Poll check_job for MCP tools marked long-running instead of calling them again"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.9
          }
        ],
        "editorialScores": {
          "ergonomics": 75,
          "maintenance": 58,
          "payments": 30,
          "reliability": 33,
          "schema": 81,
          "security": 82,
          "transparency": 65
        },
        "provenanceScore": 44,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "http": "curl https://api.edenai.run/v3/models",
        "claudeCode": "claude mcp add edenai --transport http https://mcp.edenai.run/mcp --header \"Authorization: Bearer $EDENAI_API_KEY\"",
        "config": {
          "mcpServers": {
            "edenai": {
              "headers": {
                "Authorization": "Bearer YOUR_EDENAI_API_KEY"
              },
              "url": "https://mcp.edenai.run/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/inference.router",
        "tool": "https://letme.dev/eden-ai"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Platform fee on credit purchases",
          "unit": "pct",
          "usd": 5.5,
          "note": "On top of provider list prices, which carry no markup"
        }
      ],
      "provenance": {
        "legalEntity": "Eden AI SAS",
        "domain": "edenai.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": false,
        "terms": "https://www.edenai.co/terms",
        "privacy": "https://www.edenai.co/privacy",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-11-06",
        "notes": [
          "The terms, last updated 22 October 2026, name Eden AI SAS, share capital €4,992, 19 rue Louis Guérin, 69100 Villeurbanne, France, under French law with courts in Lyon.",
          "The API and MCP server run on edenai.run, a second domain of the same company, while the site and docs are on edenai.co.",
          "robots.txt on www.edenai.co allows all agents and carries `Content-Signal: search=yes, ai-input=yes, ai-train=yes`.",
          "/.well-known/security.txt returns 404. No status page is linked, and status.edenai.co didn't resolve on 6 November 2026.",
          "RDAP for edenai.co wasn't read: rdap.org rate-limited us and the .co registry server wasn't tried."
        ],
        "score": 44
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/eden-ai.json",
      "live": {
        "slug": "eden-ai",
        "probe": {
          "target": "https://mcp.edenai.run/mcp",
          "method": "get",
          "lastAt": "2026-11-07T19:22:04.810042763Z",
          "lastOk": true,
          "lastStatus": 405,
          "lastMs": 58,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 50,
          "p95ms24h": 129,
          "samples24h": 210,
          "samples30d": 210,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "securityTxt": {
          "url": "https://edenai.co/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-11-07T15:59:41.694549385Z"
        },
        "llmsTxt": {
          "url": "https://www.edenai.co/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:20.299431316Z"
        },
        "pages": [
          {
            "url": "https://www.edenai.co/privacy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-07T14:28:13.706474894Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "21a1da47a2ce"
          },
          {
            "url": "https://www.edenai.co/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-07T14:28:15.881335606Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "9cd0db8f0f61"
          }
        ],
        "mcpTools": {
          "url": "https://mcp.edenai.run/mcp",
          "checkedAt": "2026-11-07T01:44:01.27972989Z",
          "status": "ok",
          "protocol": "2025-11-25",
          "tools": [
            {
              "name": "list_models",
              "description": "List available providers/models and their pricing.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "tool": {
                    "anyOf": [
                      {
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Optional tool name (as returned by tools/list) to filter on."
                  }
                },
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "list_voices",
              "description": "List the voices a text-to-speech model accepts, for audio_tts's 'voice'.\n\nThe model's default voice comes first.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "gender": {
                    "anyOf": [
                      {
                        "enum": [
                          "female",
                          "male",
                          "unknown"
                        ],
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Keep voices of this gender."
                  },
                  "language": {
                    "anyOf": [
                      {
                        "type": "string"
                      },
                      {
                        "type": "null"
                      }
                    ],
                    "default": null,
                    "description": "Keep voices speaking this language: 'fr' matches every region,\n'fr-CA' only that locale. Multilingual voices are always kept."
                  },
                  "limit": {
                    "default": 50,
                    "description": "Most voices to return (default 50, max 200); 'total' counts every match.",
                    "type": "integer"
                  },
                  "model": {
                    "description": "The audio_tts model, as 'provider' or 'provider/model' (e.g. 'amazon/neural').",
                    "type": "string"
                  }
                },
                "required": [
                  "model"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "upload_file",
              "description": "Upload a file to Eden AI and get a file ID to use in other tools.\n\nOnly needed for local file content. If you already have a public URL\nfor the file, pass that URL directly to the tool's file parameter\ninstead — no upload needed.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "content_base64": {
                    "description": "The file content, base64-encoded.",
                    "type": "string"
                  },
                  "expires_in_days": {
                    "default": 30,
                    "description": "How long Eden AI keeps the file (1-30, default 30).",
                    "type": "integer"
                  },
                  "filename": {
                    "description": "Name with extension (used to detect the file type).",
                    "type": "string"
                  }
                },
                "required": [
                  "content_base64",
                  "filename"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "check_job",
              "description": "Get the status/result of an async job started by a long-running tool.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "job_id": {
                    "description": "The job id returned when the job was submitted.",
                    "type": "string"
                  }
                },
                "required": [
                  "job_id"
                ],
                "type": "object"
              },
              "outputSchema": {
                "additionalProperties": true,
                "type": "object"
              }
            },
            {
              "name": "manage_collections",
              "description": "Create and manage collections: stored sets of items (e.g. faces) that a tool searches against. Tools that take a collection_id: image_face_recognition. Flow: create, then add_item once per file (returns the item ids it indexed), then call the tool with the collection_id; delete when done. Arguments per action: create(model, tool?, name?); list(tool?, model?, page?); get, delete, list_items(collection_id); add_item(collection_id, file); delete_item(collection_id, item_id).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "action": {
                    "enum": [
                      "create",
                      "list",
                      "get",
                      "delete",
                      "add_item",
                      "list_items",
                      "delete_item"
                    ],
                    "type": "string"
                  },
                  "collection_id": {
                    "description": "From create or list.",
                    "type": "string"
                  },
                  "file": {
                    "description": "File to add (add_item). Pass a file ID (UUID) from upload_file, or a direct file URL.",
                    "type": "string"
                  },
                  "item_id": {
                    "description": "Item to delete (delete_item), from add_item or list_items.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Provider the collection binds to (create; list filter). image_face_recognition: amazon.",
                    "type": "string"
                  },
                  "name": {
                    "description": "Optional label (create).",
                    "type": "string"
                  },
                  "page": {
                    "description": "Result page (list).",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "tool": {
                    "description": "Tool the collection serves (create; list filter). Defaults to image_face_recognition.",
                    "enum": [
                      "image_face_recognition"
                    ],
                    "type": "string"
                  }
                },
                "required": [
                  "action"
                ],
                "type": "object"
              }
            },
            {
              "name": "audio_speech_to_text",
              "description": "Speech Recognition (or speech to text or voice to text) can recognize and transcribe spoken words (voice),  that will be converted to text with or without diarization. It is also possible to filter profanity. The type of files allowed are: mp3, wav, m4a. If convert_to_wav option is set to true, then you can transcribe any type of audio or video files. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Audio file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: audio/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Language code in ISO format (e.g., 'en', 'fr', 'es')",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, assembly, deepgram, deepgram/base, deepgram/enhanced, deepgram/nova-3, gladia, google, gradium, gradium/stt-translate, greenpt, greenpt/green-s, greenpt/green-s-pro, microsoft, mistral, mistral/voxtral-mini-2602, mistral/voxtral-mini-latest, mistral/voxtral-mini-transcribe-3, mistral/voxtral-small-transcribe-3, openai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "profanity_filter": {
                    "default": false,
                    "description": "Whether to filter profanity and replace inappropriate words with a series of asterisks",
                    "type": "boolean"
                  },
                  "speakers": {
                    "default": 2,
                    "description": "Number of speakers present in the audio",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "vocabulary": {
                    "description": "List of words or composed words to be detected by the speech to text engine",
                    "items": {
                      "type": "string"
                    },
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "audio_tts",
              "description": "Text-to-speech (TTS) is a technology that converts written text into spoken audio, enabling computers and digital devices to \"read\" text aloud.  It is also known as speech synthesis, read aloud technology, or computer-generated speech.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "audio_format": {
                    "description": "Desired audio format (e.g., 'mp3', 'wav')",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon/neural, amazon/standard, deepgram/aura, deepgram/aura-2, elevenlabs, elevenlabs/eleven_flash_v2, elevenlabs/eleven_flash_v2_5, elevenlabs/eleven_multilingual_v2, elevenlabs/eleven_turbo_v2, elevenlabs/eleven_turbo_v2_5, elevenlabs/eleven_v3, google/casual, google/chirp-hd, google/chirp3-hd, google/gemini-2.5-flash-tts, google/gemini-2.5-pro-tts, google/gemini-3.1-flash-tts-preview, google/neural2, google/news, google/polyglot, google/standard, google/studio, google/wavenet, gradium, microsoft/neural, microsoft/neural-hd, mistral/voxtral-mini-tts-3, openai/gpt-4o-mini-tts, openai/tts-1, openai/tts-1-hd, ovhcloud/nvr-tts-de-de, ovhcloud/nvr-tts-en-us, ovhcloud/nvr-tts-es-es, ovhcloud/nvr-tts-it-it. Call list_models for pricing.",
                    "type": "string"
                  },
                  "speaking_pitch": {
                    "description": "Increase or decrease the speaking pitch by a percentage from -100% to 100%, 0 is normal.",
                    "maximum": 100,
                    "minimum": -100,
                    "type": "integer"
                  },
                  "speaking_volume": {
                    "description": "Increase or decrease the audio volume by a percentage from -100% to 100%, 0 is normal.",
                    "maximum": 100,
                    "minimum": -100,
                    "type": "integer"
                  },
                  "speed": {
                    "description": "Speed multiplier for speech synthesis",
                    "maximum": 4,
                    "minimum": 0.25,
                    "type": "number"
                  },
                  "text": {
                    "description": "Text to convert to speech",
                    "minLength": 1,
                    "type": "string"
                  },
                  "voice": {
                    "description": "Voice to synthesize with: an id or name from list_voices(model=...), matched case-insensitively. Omit it to use the model's default voice. An id the list doesn't know (e.g. your own cloned voice) is sent to the provider unchanged.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_ai_detection",
              "description": "Determine whether an image was generated by AI or is a real photograph or artwork. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble, winstonai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_anonymization",
              "description": "Image Anonymization API, also known as image de-identification or image de-personalization, refers to the process of automatically removing personal or sensitive information from images. The main objective is to protect the privacy and security of individuals who may be depicted in images shared online or used for research purposes. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_background_removal",
              "description": "Background removal is a digital image processing technique designed to seamlessly eliminate the backdrop of a photo, leaving behind only the main subject. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai, clipdrop, photoroom, picsart, sentisight, stabilityai. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_deepfake_detection",
              "description": "Detect whether a face in a real photo has been swapped or manipulated (face-swap deepfakes). For fully AI-generated images, use AI Image Detection instead. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble, sightengine. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_explicit_content",
              "description": "Explicit Content Detection detects adult only content in images, that is generally inappropriate for people under the age of 18 and includes nudity, sexual activity, pornography, violence, gore content, etc. (type of files allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, google, microsoft, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_compare",
              "description": "Compare two faces and decide whether they are from the same person. The API expects 2 images, reference and query, where the former is the ground truth (e.g. user's official ID) and the latter is the validation image (e.g. a selfie). File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file1": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "file2": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, base64, facepp. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file1",
                  "file2"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_detection",
              "description": "Face Detection is a computer technology being used in a variety of applications that identifies human faces in digital images with different attributes like landmarks, sentiments and physical attire (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_face_recognition",
              "description": "Recognizing a face in an image is a more advanced feature than just detecting the face in the image. It allows the user to search for the detected face from a database of existing images and extract the faces that are most similar to the face displayed in the query image. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "collection_id": {
                    "description": "Id of one of your collections. Make one with manage_collections (action='create', then add_item for each file to search against); action='list' shows the ones you have. 'model' must be the collection's provider.",
                    "type": "string"
                  },
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "collection_id",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_generation",
              "description": "Image Generation is an advanced feature that generates compelling images based on a given text prompt. It can easily produce high-quality and original images in a matter of seconds, without the need for specialized design skills or software File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "mask": {
                    "description": "Optional inpainting mask. Must be paired with at least one reference image (otherwise the request returns 422). Support varies by model; models that do not accept a mask surface the error as status=\"fail\" with a provider message in the response body. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: bytedance, bytedance/seedream-4-0-250828, bytedance/seedream-4-5-251128, bytedance/seedream-5-0-260128, google, google/gemini-2.5-flash-image, google/gemini-3-pro-image-preview, infomaniak/flux, ionos/black-forest-labs/FLUX.1-schnell, ionos/black-forest-labs/FLUX.2-klein-4B, leonardo, leonardo/AlbedoBase XL, leonardo/Leonardo Anime XL, leonardo/Leonardo Diffusion XL, leonardo/Leonardo Kino XL, leonardo/Leonardo Lightning XL, leonardo/Leonardo Phoenix, leonardo/Leonardo Vision XL, leonardo/SDXL 0.9, minimax, minimax/image-01, openai, openai/gpt-image-1, openai/gpt-image-1-mini, openai/gpt-image-1.5, openai/gpt-image-2, ovhcloud/stable-diffusion-xl-base-v10, pruna/p-image, pruna/p-image-edit, pruna/p-image-ideogram, pruna/p-image-ideogram-low, pruna/p-image-ideogram-medium, pruna/p-image-ideogram-very-high, pruna/p-image-ideogram-very-low, replicate, replicate/anime-style, replicate/classic, replicate/vintedois-diffusion, stabilityai, stabilityai/stable-diffusion-xl-1024-v1-0. Call list_models for pricing.",
                    "type": "string"
                  },
                  "num_images": {
                    "default": 1,
                    "description": "Number of images to generate",
                    "maximum": 10,
                    "minimum": 1,
                    "type": "integer"
                  },
                  "reference_images": {
                    "description": "Optional reference images. Plain file IDs/URLs are treated as ReferenceImage with kind=None. Support and per-model limits vary by model; models that do not accept reference images surface the error as status=\"fail\" with a provider message in the response body.",
                    "items": {},
                    "maxItems": 64,
                    "type": "array"
                  },
                  "resolution": {
                    "description": "Image resolution as a named size (e.g. '1024x1024'). Optional: providers may also accept native sizing knobs (width/height, aspect_ratio, image_size tier, etc.) in the top-level `provider_params` request field, next to `input` rather than inside it, in which case `provider_params` takes precedence.",
                    "pattern": "^\\d+x\\d+$",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text prompt for image generation",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_logo_detection",
              "description": "Logo Detection is a powerful technology that enables the automatic identification and recognition of popular logos within an image. It provides accurate and efficient detection of known (and less known) brand logos. It's a valuable tool for a variety of industries, including advertising, retail, and e-commerce. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: api4ai, api4ai/v1, api4ai/v2, google, microsoft, openai, openai/gpt-4-turbo, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "image_object_detection",
              "description": "Object Detection is a computer vision technique that allows users to identify and locate (with bounding boxes) objects in an image. The detected objects can be animals, people, electronics, vehicles etc. (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, microsoft, sentisight. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr",
              "description": "Optical Character Recognition or Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text. The image can be a scanned document or a photo of a license plate, a road sign or anything else that contains text (type of files allowed: jpg, jpeg, png, tiff) . File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, ionos, ionos/lightonai/LightOnOCR-2-1B, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest, sentisight. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_async",
              "description": "OCR or Optical Character Recognition is also referred to as text recognition or text extraction. It allows users to extract text data from PDFs with multiple pages. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_financial_parser",
              "description": "Financial Parser API is a powerful and versatile tool designed to streamline your financial data extraction process. This cutting-edge API combines Optical Character Recognition (OCR) technology with advanced parsing capabilities to seamlessly extract and organize relevant information from invoices and receipts. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "document_type": {
                    "default": "invoice",
                    "description": "Specify the type of your document. Can be set to 'auto-detect' for automatic detection if the provider supports it.",
                    "enum": [
                      "auto-detect",
                      "invoice",
                      "receipt"
                    ],
                    "type": "string"
                  },
                  "file": {
                    "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.",
                    "type": "string"
                  },
                  "language": {
                    "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, eagledoc, extracta, google, klippa, microsoft, mindee, openai, openai/gpt-4o, tabscanner, veryfi. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_identity_parser",
              "description": "ID Document parsing technology allows users to automatically extract information from an ID Document such as passport, ID card, driving license and more. This API is ideal for developers looking to create applications that require identity verification or access control. It extracts information like name, date of birth, nationality, age and more. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, klippa, microsoft, mindee, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_resume_parser",
              "description": "Resume Parser enables users to extract various information from resumes (curriculum vitae, CV) that could be in a variety of formats and returns structured data (name, job list, education, skills) to automate their processing. (type of files allowed: pdf, jpg, jpeg, png) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: affinda, extracta, klippa, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "ocr_tables",
              "description": "OCR Table (Optical Character Recognition for tabular documents)  allows users to analyze documents containing tables and returns a structured representation of the detected tables in the form of a Json object that can be converted to a CSV. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, google, microsoft. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_ai_detection",
              "description": "The AI Detection API is a tool designed to determine whether a given text was generated by an artificial intelligence chatbot, or a Language Model (LLM).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: sapling, winstonai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for AI detection, at least 300 characters long. Shorter texts carry too little signal to be scored reliably.",
                    "minLength": 300,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_anonymization",
              "description": "The personally identifiable information (PII) detection feature can identify and redact sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Removing these personally identifiable information helps with the Anonymization of a text and privacy protection.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, limina, microsoft. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to detect personal information in",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_moderation",
              "description": "Text moderation scans text for offensive, sexually explicit or suggestive content, it also checks if there is any content of self-harm, violence, racist or hate speech.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: google, microsoft, openai, openai/text-moderation-007, openai/text-moderation-latest, openai/text-moderation-stable, ovhcloud/Qwen3Guard-Gen-0.6B, ovhcloud/Qwen3Guard-Gen-8B. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to moderate",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_named_entity_recognition",
              "description": "Named Entity Recognition (also called entity identification or extraction) is an information extraction technique that automatically identifies named entities in a text and classifies them into predefined categories such as dates, persons names, company names, dates, products etc.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, microsoft, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for named entities",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_plagia_detection",
              "description": "The Plagiarism Detection API is a tool designed to scan a content string for plagiarism using a plagiarism detection module",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: winstonai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text content on which plagiarism detection will be run",
                    "minLength": 1,
                    "type": "string"
                  },
                  "title": {
                    "description": "Content title",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_spell_check",
              "description": "Spell Check analyzes the inputted text by comparing it to a dictionary of correctly spelled words to identify and highlight any spelling errors or grammatical mistakes.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: prowritingaid, sapling. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to be spell-checked",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "text_topic_extraction",
              "description": "Topic analysis is a Natural Language Processing (NLP) technique that allows us to automatically extract meaning from text by identifying recurrent themes or topics.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "language": {
                    "description": "ISO 639-1 language code",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: google, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to analyze for topics",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "translation_automatic_translation",
              "description": "Automatic translation or machine translation (MT) is the process of automatically translating a text from one language to another language. The aim of it is to enable people to communicate and access information in different languages, without the need for a human translator.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: amazon, deepl, google, microsoft, modernmt, openai, openai/gpt-4o. Call list_models for pricing.",
                    "type": "string"
                  },
                  "source_language": {
                    "description": "Source language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "target_language": {
                    "description": "Target language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "text": {
                    "description": "Text to translate",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text",
                  "target_language"
                ],
                "type": "object"
              }
            },
            {
              "name": "translation_document_translation",
              "description": "Document Translation API translates whole documents in supported languages and various file formats (like pdf or doc) while keeping their structure intact. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Document file ID from /v3/upload or direct file URL (PDF, DOCX, PPTX) Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/vnd.openxmlformats-officedocument.presentationml.presentation.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepl, google. Call list_models for pricing.",
                    "type": "string"
                  },
                  "source_language": {
                    "description": "Source language code",
                    "minLength": 1,
                    "type": "string"
                  },
                  "target_language": {
                    "description": "Target language code",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file",
                  "target_language"
                ],
                "type": "object"
              }
            },
            {
              "name": "video_deepfake_detection",
              "description": "Detect deepfake and synthetically manipulated video. Returns an overall deepfake score and prediction, along with per-frame scores when the provider supplies them. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "file": {
                    "description": "Video file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: resemble. Call list_models for pricing.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "file"
                ],
                "type": "object"
              }
            },
            {
              "name": "video_generation",
              "description": "The Video Generation API enables easy creation of high-quality videos from text,and images, perfect for marketing, education, and more—all through one integration. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "dimension": {
                    "default": "1280x720",
                    "description": "Video resolution in 'widthxheight' format (e.g., '1280x720')",
                    "pattern": "^\\d+x\\d+$",
                    "type": "string"
                  },
                  "duration": {
                    "description": "Length of the generated video in seconds. Omit to use the model's default duration.",
                    "maximum": 120,
                    "minimum": 1,
                    "type": "integer"
                  },
                  "file": {
                    "description": "Initial keyframe image (JPEG or PNG) file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/jpeg, image/png.",
                    "type": "string"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: bytedance, bytedance/dreamina-seedance-2-0-260128, bytedance/dreamina-seedance-2-0-fast-260128, bytedance/dreamina-seedance-2-0-mini-260615, bytedance/dreamina-seedance-2-5-260628, bytedance/seedance-1-0-pro-250528, bytedance/seedance-1-0-pro-fast-251015, bytedance/seedance-1-5-pro-251215, minimax, minimax/MiniMax-Hailuo-02, minimax/MiniMax-Hailuo-2.3, minimax/S2V-01, minimax/T2V/I2V-01-Director, openai, openai/sora-2, openai/sora-2-pro, pixverse, pixverse/c1, pixverse/v5, pixverse/v5.5, pixverse/v6, pruna, pruna/p-video, pruna/p-video-2, pruna/p-video-2-pro, pruna/p-video-2-pro-cost, pruna/p-video-2-pro-quality, pruna/p-video-animate, pruna/p-video-avatar, pruna/p-video-edit, xai/grok-imagine-video-1.5, xai/grok-imagine-video-1.5-lite. Call list_models for pricing.",
                    "type": "string"
                  },
                  "seed": {
                    "description": "Random seed for generation reproducibility (0 to 2,147,483,646). Omit for varied output.",
                    "maximum": 2147483646,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "text": {
                    "description": "Text prompt describing the content and style of the video to generate",
                    "minLength": 1,
                    "type": "string"
                  },
                  "video": {
                    "description": "Source video to edit, for models that edit a video (their `requires_video` is true in /v3/info). The output keeps the source's length, which is what is billed, so `duration` and `dimension` do not apply to them. Other models refuse it. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.",
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "text"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_batch_scrape",
              "description": "Scrape many URLs in one request and return each page's content. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.",
                    "type": "string"
                  },
                  "urls": {
                    "description": "Explicit list of URLs to scrape (async job)",
                    "items": {
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "urls"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_crawl",
              "description": "Crawl a site from a starting URL and return the content of its pages. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "Root URL to crawl (async job)",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_map",
              "description": "Discover and return the list of URLs on a site (a sitemap-style link map).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "Root URL to map (discover its links)",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_research",
              "description": "Run deep, multi-step web research on a query and return a synthesized answer with sources. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl, linkup, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "prompt": {
                    "description": "Natural-language research task for the agent",
                    "minLength": 1,
                    "type": "string"
                  },
                  "reasoning_depth": {
                    "default": "L",
                    "description": "Research reasoning-effort tier (billed per tier; priced pre-call)",
                    "enum": [
                      "S",
                      "M",
                      "L",
                      "XL"
                    ],
                    "type": "string"
                  },
                  "schema": {
                    "description": "JSON schema describing the structured output",
                    "type": "object"
                  }
                },
                "required": [
                  "model",
                  "prompt"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_scraping",
              "description": "Fetch a single URL and return its clean content as markdown, text, or HTML, with optional JavaScript rendering.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, tavily. Call list_models for pricing.",
                    "type": "string"
                  },
                  "url": {
                    "description": "URL of the web page to scrape",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "url"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_search",
              "description": "Search the web for a query and return ranked results (title, URL, and a snippet or the page content).",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "depth": {
                    "default": "standard",
                    "description": "Search depth tier. `deep` is refused with a 400 on deepseek, perplexityai and zai, which run one tier only.",
                    "enum": [
                      "standard",
                      "deep"
                    ],
                    "type": "string"
                  },
                  "max_results": {
                    "description": "Max number of search results to return",
                    "minimum": 1,
                    "type": "integer"
                  },
                  "model": {
                    "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, perplexityai, tavily, zai. Call list_models for pricing.",
                    "type": "string"
                  },
                  "query": {
                    "description": "The web search query",
                    "minLength": 1,
                    "type": "string"
                  }
                },
                "required": [
                  "model",
                  "query"
                ],
                "type": "object"
              }
            },
            {
              "name": "web_structured_extraction",
              "description": "Extract structured data from one or more web pages against a schema or prompt. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.",
              "inputSchema": {
                "additionalProperties": false,
                "properties": {
                  "model": {
                    "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.",
                    "type": "string"
                  },
                  "prompt": {
                    "description": "Natural-language description of what to extract",
                    "type": "string"
                  },
                  "schema": {
                    "description": "JSON schema describing the structured output",
                    "type": "object"
                  },
                  "urls": {
                    "description": "URLs to extract structured data from (async job)",
                    "items": {
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                },
                "required": [
                  "model",
                  "urls"
                ],
                "type": "object"
              }
            }
          ],
          "schemaTokens": 10725,
          "changedAt": "2026-11-07T01:44:01.27972989Z",
          "check": {
            "checker": "anchor-check/1.0",
            "totalTokens": 10725,
            "counts": {
              "error": 0,
              "note": 1,
              "warn": 49
            },
            "findings": [
              {
                "rule": "TC11",
                "severity": "warn",
                "tool": "manage_collections",
                "message": "1 parameter without a description: action",
                "fix": "Describe each one: format, units, an example, and what happens when it's left out."
              },
              {
                "rule": "TC12",
                "severity": "warn",
                "tool": "image_generation",
                "message": "no type for reference_images[]",
                "fix": "Give every parameter a type (or an enum)."
              },
              {
                "rule": "TC13",
                "severity": "warn",
                "tool": "web_research",
                "message": "schema (object with no properties)",
                "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
              },
              {
                "rule": "TC13",
                "severity": "warn",
                "tool": "web_structured_extraction",
                "message": "schema (object with no properties)",
                "fix": "Declare the properties (or additionalProperties with a schema) and the array's items."
              },
              {
                "rule": "TC14",
                "severity": "warn",
                "tool": "image_face_recognition",
                "message": "allowed values are in the description, not an enum: collection_id",
                "fix": "Move them into enum."
              },
              {
                "rule": "TC14",
                "severity": "warn",
                "tool": "image_generation",
                "message": "allowed values are in the description, not an enum: resolution",
                "fix": "Move them into enum."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "audio_speech_to_text",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "audio_tts",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "check_job",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_ai_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_anonymization",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_background_removal",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_deepfake_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_explicit_content",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_compare",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_face_recognition",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_generation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_logo_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "image_object_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "list_models",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "list_voices",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "manage_collections",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_async",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_financial_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_identity_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_resume_parser",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "ocr_tables",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_ai_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_anonymization",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_moderation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_named_entity_recognition",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_plagia_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_spell_check",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "text_topic_extraction",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "translation_automatic_translation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "translation_document_translation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "upload_file",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "video_deepfake_detection",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "video_generation",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_batch_scrape",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_crawl",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_map",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_research",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_scraping",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_search",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking."
              },
              {
                "rule": "TC16",
                "severity": "warn",
                "tool": "web_structured_extraction",
                "message": "no readOnlyHint or destructiveHint",
                "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint."
              },
              {
                "rule": "TC23",
                "severity": "warn",
                "message": "42 tools",
                "fix": "Offer a smaller default toolset and let clients opt into the rest."
              },
              {
                "rule": "TC24",
                "severity": "note",
                "message": "38 of 42 tools have no outputSchema",
                "fix": "Declare outputSchema for tools that return structured data, and return structuredContent that matches it."
              }
            ]
          }
        },
        "updatedAt": "2026-11-07T19:22:04.810042763Z"
      }
    },
    "answer": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments \u0026 pricing.",
    "b": {
      "slug": "xai-api",
      "name": "xAI API (Grok)",
      "vendor": "SpaceXSI (xAI)",
      "vendorUrl": "https://x.ai",
      "kind": "model",
      "category": "inference",
      "summary": "xAI's API for its Grok models (the docs now name the company SpaceXSI), with text, image, video and voice endpoints, server-side search and remote MCP tools, through an OpenAI-compatible REST API or gRPC.",
      "url": "https://www.anchorterminal.com/tools/xai-api",
      "markdownUrl": "https://www.anchorterminal.com/tools/xai-api.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/xai-api.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/xai-api.json",
      "dns": "xai-api.grade.anchorterminal.com",
      "repo": "https://github.com/xai-org/xai-sdk-python",
      "license": "Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.x.ai/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "xai-sdk"
        }
      ],
      "auth": "api-key",
      "authNotes": "`Authorization: Bearer` with a team API key from console.x.ai. Keys can be limited to endpoints and models by ACL, capped by QPM and TPM, given an expiry, and rotated or disabled through the Management API. mTLS is documented as an option, and GitHub secret scanning disables leaked keys.",
      "pricing": "usage",
      "pricingNotes": "Prepaid credits, then the default payment method at month end. Grok 4.7 costs $2 input, $0.50 cached input and $6 output per 1M tokens below 200K prompt tokens, and $4/$1/$12 above, applied to the whole request. Batch is 20% off on grok-4.7, 4.6, 4.5, 4.3 and the grok-4.20 models. Priority processing 2x, the US regional endpoint 1.1x. Web search, code execution and attachment search $5 per 1,000 calls, collections search $2.50, X search $5 per 1,000 posts. $0.05 fee for a request blocked before generation for a usage-policy violation (https://docs.x.ai/developers/pricing, checked 2026-11-06).",
      "priceSummary": "from $1.25 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs, llms.txt or the OpenAPI spec. Access needs a console account loaded with prepaid credits (checked 2026-11-06).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 597,
        "npmWeekly": null,
        "pypiWeekly": 912149,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://docs.x.ai",
      "rateLimitsUrl": "https://docs.x.ai/developers/rate-limits",
      "llmsTxt": "https://docs.x.ai/llms.txt",
      "openapi": "https://docs.x.ai/openapi.json",
      "capabilities": [
        "inference.llm"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "prepaid",
        "openapi",
        "llms-txt",
        "openai-compatible",
        "closed-source",
        "python",
        "batch",
        "status-page",
        "bug-bounty",
        "soc2"
      ],
      "lastRelease": "2026-11-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 71.7,
        "grade": "BB",
        "agentReady": true,
        "rank": 152,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 8,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 90,
          "maintenance": 77,
          "payments": 20,
          "reliability": 55,
          "schema": 88,
          "security": 97,
          "transparency": 63
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.",
        "bestFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.",
        "strengths": [
          "Grok 4.7 at $2/$6 per million tokens below 200K prompt tokens, with a 500K context and 20% off through the Batch API",
          "API keys restricted by endpoint and model ACLs, with QPM and TPM caps, expiry and a rotate endpoint",
          "Self-serve team-wide zero data retention, confirmed on every response by an `x-zero-data-retention` header",
          "OpenAPI 3.1 spec, llms.txt and a Markdown twin of every docs page",
          "security.txt valid to 2027-06-29 and a HackerOne bug bounty"
        ],
        "weaknesses": [
          "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August",
          "No SLA, no free tier for the text API, and no Retry-After header documented for 429s",
          "No stated minimum notice for retirements, and retired slugs are served by a different model at its price",
          "Remote MCP doesn't support `require_approval`, so server-side tool calls run without an approval step",
          "The terms, privacy policy and DPA at x.ai/legal answered a Cloudflare block on 6 October and 6 November 2026, so they weren't read"
        ],
        "agentNotes": [
          "Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated",
          "Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price",
          "Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2",
          "Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context",
          "Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "BB",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 71.7
          }
        ],
        "editorialScores": {
          "ergonomics": 90,
          "maintenance": 77,
          "payments": 20,
          "reliability": 55,
          "schema": 88,
          "security": 97,
          "transparency": 52
        },
        "provenanceScore": 73,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install xai-sdk   # or: pip install openai, with base_url https://api.x.ai/v1",
        "http": "curl https://api.x.ai/v1/responses \\\n  -H \"Authorization: Bearer $XAI_API_KEY\" -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"grok-4.7\",\"input\":\"What is the meaning of life?\"}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/xai-api"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Web search tool",
          "unit": "1k-requests",
          "usd": 5
        },
        {
          "item": "Code execution tool",
          "unit": "1k-requests",
          "usd": 5
        },
        {
          "item": "Collections search tool",
          "unit": "1k-requests",
          "usd": 2.5
        }
      ],
      "provenance": {
        "legalEntity": "",
        "domain": "x.ai",
        "domainRegistered": "2017-12-16",
        "domainNote": "x.ai was registered in 2017, before the company, and transferred on 2026-06-02 per RDAP. Every x.ai page except robots.txt and security.txt answered a Cloudflare block page (403) on 2026-11-06, as the legal pages did on 2026-10-06, so the contracting entity wasn't confirmed. The docs now use the name SpaceXSI and the status page SpaceXAI.",
        "endpointOnVendorDomain": true,
        "terms": "https://x.ai/legal/terms-of-service-enterprise",
        "privacy": "https://x.ai/legal/privacy-policy",
        "statusPage": "https://status.x.ai",
        "changelog": "https://docs.x.ai/developers/release-notes",
        "securityTxt": "valid",
        "checked": "2026-11-06",
        "notes": [
          "x.ai/robots.txt allows all but /tools/, with Content-Signal ai-train=yes, search=yes, ai-input=yes. docs.x.ai allows all with ai-input=yes. The x.ai pages that robots.txt allows answered a Cloudflare 'Attention Required' page, which we did not try to get past.",
          "security.txt at x.ai/.well-known/security.txt is valid to 2027-06-29, with vulnerabilities@x.ai and abuse@x.ai."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/xai-api.json",
      "live": {
        "slug": "xai-api",
        "probe": {
          "target": "https://api.x.ai/v1",
          "method": "get",
          "lastAt": "2026-11-07T19:22:45.426736159Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 193,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 178,
          "p95ms24h": 276,
          "samples24h": 210,
          "samples30d": 210,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.x.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-11-07T04:49:01.143662157Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "xai-org/xai-sdk-python",
            "version": "v1.21.0",
            "released": "2026-10-23",
            "seenAt": "2026-11-07T00:18:15.193708838Z"
          },
          {
            "registry": "pypi",
            "name": "xai-sdk",
            "version": "1.21.0",
            "released": "2026-10-23",
            "seenAt": "2026-11-07T00:18:15.09038487Z"
          }
        ],
        "githubStars": 598,
        "pypiWeekly": 912149,
        "securityTxt": {
          "url": "https://x.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2027-06-29T00:00:00.000Z",
          "checkedAt": "2026-11-07T16:01:43.978620532Z"
        },
        "llmsTxt": {
          "url": "https://docs.x.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:34:24.762831371Z"
        },
        "pages": [
          {
            "url": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:46.034096807Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "1238569c8142"
          },
          {
            "url": "https://docs.x.ai/developers/migration/may-15-retirement",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:48.207542223Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "813d0e188a0e"
          },
          {
            "url": "https://docs.x.ai/developers/release-notes",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:52.143682141Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "7b37cfaf2576"
          },
          {
            "url": "https://docs.x.ai/developers/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-11-07T14:08:50.158330981Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "a563de9617fe"
          },
          {
            "url": "https://x.ai/legal/privacy-policy",
            "kind": "privacy",
            "status": 403,
            "checkedAt": "2026-11-07T14:38:04.991061235Z",
            "changedAt": "0001-01-01T00:00:00Z"
          },
          {
            "url": "https://x.ai/legal/terms-of-service-enterprise",
            "kind": "terms",
            "status": 403,
            "checkedAt": "2026-11-07T14:38:09.200382604Z",
            "changedAt": "0001-01-01T00:00:00Z"
          }
        ],
        "updatedAt": "2026-11-07T19:22:45.426736159Z"
      }
    },
    "edges": [
      {
        "by": 22,
        "category": "reliability",
        "leads": "xai-api",
        "name": "Reliability",
        "reasons": {
          "a": "Router, read on the hosted lines. No status page is linked from the site or docs, and status.edenai.co didn't resolve for us on 6 November 2026 (0). No incident history to read (5). The rate-limits page gives 10 requests a second per account, shared across keys, while the plans page gives 7 a second, raisable to 15, so the figure is documented but inconsistent (10). Fallback retries the next model or provider on a 429 or error inside one request, but no client-facing 429 or Retry-After guidance was found (8). No SLA published; 'Dedicated support \u0026 SLA' is listed only for the custom Advanced plan, and the pricing page's '99.99%' uptime is a claim without a status page behind it (0). The v3 API is GA (10). 0+5+10+8+0+10 = 33.",
          "b": "Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10)."
        },
        "scores": {
          "a": 33,
          "b": 55
        }
      },
      {
        "by": 19,
        "category": "maintenance",
        "leads": "xai-api",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.",
          "b": "Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10)."
        },
        "scores": {
          "a": 58,
          "b": 77
        }
      },
      {
        "by": 15,
        "category": "ergonomics",
        "leads": "xai-api",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.",
          "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15)."
        },
        "scores": {
          "a": 75,
          "b": 90
        }
      },
      {
        "by": 15,
        "category": "security",
        "leads": "xai-api",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.",
          "b": "Model reading. Team API keys with ACLs per endpoint and per model, QPM and TPM caps, expiry, and create, rotate, disable and delete through the Management API, plus documented mTLS. GitHub secret scanning disables leaked keys and emails the owner (30). The security FAQ says SpaceXSI never trains on API inputs or outputs without explicit permission (20). Requests and responses are kept 30 days for abuse auditing, then deleted, and team admins can switch on zero data retention themselves, confirmed by an `x-zero-data-retention` header on every response (15). Console audit log and a Management API audit-events endpoint, plus optional per-key request logging (15). security.txt valid to 2027-06-29 with a HackerOne bug bounty and a separate safety contact for prompt-injection issues. SOC 2 Type 2 is claimed in the security FAQ with the reports behind an NDA in the trust centre, so 17 of 20. Remote MCP doesn't support `require_approval`, which the model checklist doesn't score but reviewers should see. New in October, a `guidelines` array lets the caller make the model decline nsfw, violence or profanity content, which the checklist doesn't score."
        },
        "scores": {
          "a": 82,
          "b": 97
        }
      },
      {
        "by": 10,
        "category": "payments",
        "leads": "eden-ai",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.",
          "b": "No x402, MPP or L402 (0). Per-token and per-call prices published without a login on docs.x.ai/developers/pricing (20). No free tier found for the text API, and the quickstart says to load the account with credits (0). Sign-up is in the browser at console.x.ai. The Management API can create keys and top up prepaid credit, but only with a management key made by a person in the console, so no line credit (0)."
        },
        "scores": {
          "a": 30,
          "b": 20
        }
      },
      {
        "by": 8,
        "category": "transparency",
        "leads": "xai-api",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Editorial half only. Closed service under terms last updated 22 October 2026, naming Eden AI SAS and French law with courts in Lyon (15). The data retention page, terms and DPA agree that content isn't stored by default, and the docs carry a per-provider table of training, retention and ZDR (27). No deprecation policy found; models are dropped in docs updates without dated notice that we found (5). The DPA's Annex 2 names operational subprocessors (AWS EMEA, ClickHouse, Sentry, Metabase, Stripe, Brevo and others) with their roles, and the EU endpoint keeps routing in the EU (18). 15+27+5+18 = 65.",
          "b": "Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20)."
        },
        "scores": {
          "a": 55,
          "b": 63
        }
      }
    ],
    "facts": [
      {
        "a": "Model router",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Eden AI SAS",
        "b": "SpaceXSI (xAI)",
        "name": "Vendor"
      },
      {
        "a": "https://mcp.edenai.run/mcp",
        "b": "https://api.x.ai/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, Streamable HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "none",
        "b": "Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-11-05",
        "b": "2026-11-02",
        "name": "Last release"
      },
      {
        "a": "2026-10-22",
        "b": "2026-10-27",
        "name": "Terms last updated"
      },
      {
        "a": "2026-10-22",
        "b": "2026-10-27",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "597 stars, 912k PyPI/wk",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Eden AI or xAI API (Grok)?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Eden AI and xAI API (Grok) need an API key?"
      },
      {
        "answer": "Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and xAI API (Grok) at https://api.x.ai/v1.",
        "question": "Can an agent call Eden AI and xAI API (Grok) without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Payments \u0026 pricing, 30 against 20"
        ],
        "also": null,
        "goodFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.",
        "slug": "eden-ai",
        "watchFor": "No public status page, incident history or SLA found"
      },
      {
        "aheadOn": [
          "Reliability, 55 against 33",
          "Schema \u0026 documentation, 88 against 81",
          "Agent ergonomics, 90 against 75",
          "Security \u0026 auth, 97 against 82",
          "Maintenance \u0026 community, 77 against 58",
          "Transparency \u0026 trust, 63 against 55"
        ],
        "also": [
          "Agent-ready, a grade of BB or better"
        ],
        "goodFor": "Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.",
        "slug": "xai-api",
        "watchFor": "API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August"
      }
    ],
    "history": null,
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.json",
        "title": "Amazon Bedrock vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.json",
        "title": "Amazon Bedrock vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.json",
        "title": "Claude API vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.json",
        "title": "Claude API vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-xai-api.json",
        "title": "Antseed vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.json",
        "title": "Azure OpenAI in Foundry Models vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.json",
        "title": "Azure OpenAI in Foundry Models vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.json",
        "title": "BlockRun.AI vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api.json",
        "title": "BlockRun.AI vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.json",
        "title": "Cerebras Inference vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api.json",
        "title": "Cerebras Inference vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai.json",
        "title": "Cloudflare AI Gateway vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-xai-api.json",
        "title": "Cloudflare AI Gateway vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai.json",
        "title": "Cloudflare Workers AI vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-xai-api.json",
        "title": "Cloudflare Workers AI vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai.json",
        "title": "Cohere Chat API (Command models) vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api.json",
        "title": "Cohere Chat API (Command models) vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai.json",
        "title": "DeepInfra vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-xai-api.json",
        "title": "DeepInfra vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai.json",
        "title": "DeepSeek API vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-xai-api.json",
        "title": "DeepSeek API vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse.json",
        "title": "Eden AI vs Glimpse",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse"
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      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.json",
        "title": "Eden AI vs Fireworks AI Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api.json",
        "title": "Eden AI vs Gemini Developer API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-groq.json",
        "title": "Eden AI vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.json",
        "title": "Eden AI vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.json",
        "title": "Eden AI vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.json",
        "title": "Eden AI vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api.json",
        "title": "Eden AI vs MiniMax API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api.json",
        "title": "Eden AI vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.json",
        "title": "Eden AI vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl.json",
        "title": "Eden AI vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.json",
        "title": "Eden AI vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json",
        "title": "Eden AI vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference.json",
        "title": "Eden AI vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.json",
        "title": "Eden AI vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.json",
        "title": "Eden AI vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.json",
        "title": "Eden AI vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.json",
        "title": "Eden AI vs Simplismart",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.json",
        "title": "Eden AI vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash.json",
        "title": "Eden AI vs SWE-2 Flash",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.json",
        "title": "Eden AI vs Together AI Inference",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.json",
        "title": "Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-xai-api.json",
        "title": "Glimpse vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-xai-api.json",
        "title": "Fireworks AI Inference vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/groq-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/jais-3-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api.json",
        "title": "Mistral AI API vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/mistral-api-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api.json",
        "title": "Muse Spark Open vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api.json",
        "title": "Nemotron 3.5 Super VL vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api.json",
        "title": "Novita AI vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api.json",
        "title": "OpenAI API vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/openai-api-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api.json",
        "title": "OpenRouter vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/openrouter-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api.json",
        "title": "Prism Inference vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/prism-inference-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api.json",
        "title": "Router.com (Ramp Router) vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/ramp-router-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json",
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        "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api"
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      {
        "json": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api.json",
        "title": "RouterPlus vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/routerplus-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api.json",
        "title": "SambaCloud vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/sambanova-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api.json",
        "title": "SiliconFlow vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/siliconflow-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api.json",
        "title": "Simplismart vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api.json",
        "title": "StepFun API vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api.json",
        "title": "SWE-2 Flash vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/swe-2-flash-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api.json",
        "title": "Tencent Cloud TokenHub vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api.json",
        "title": "Together AI Inference vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/together-inference-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api.json",
        "title": "Vercel AI Gateway vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/vercel-ai-gateway-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api.json",
        "title": "Vertex AI (Gemini Enterprise Agent Platform) vs xAI API (Grok)",
        "url": "https://www.anchorterminal.com/compare/vertex-ai-vs-xai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai.json",
        "title": "Antseed vs Eden AI",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.json",
        "title": "Eden AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm.json",
        "title": "Eden AI vs LiteLLM",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter.json",
        "title": "Eden AI vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router.json",
        "title": "Eden AI vs Router.com (Ramp Router)",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus.json",
        "title": "Eden AI vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub.json",
        "title": "Eden AI vs Tencent Cloud TokenHub",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub"
      },
      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.json",
        "title": "Eden AI vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway"
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        "eden-ai": 33,
        "edge": "xai-api",
        "key": "reliability",
        "name": "Reliability",
        "weight": 16,
        "xai-api": 55
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 7,
        "eden-ai": 81,
        "edge": "xai-api",
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13,
        "xai-api": 88
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      {
        "by": 15,
        "eden-ai": 75,
        "edge": "xai-api",
        "key": "ergonomics",
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        "weight": 13,
        "xai-api": 90
      },
      {
        "by": 15,
        "eden-ai": 82,
        "edge": "xai-api",
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14,
        "xai-api": 97
      },
      {
        "by": 10,
        "eden-ai": 30,
        "edge": "eden-ai",
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10,
        "xai-api": 20
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        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
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        "eden-ai": 58,
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        "weight": 7,
        "xai-api": 77
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        "by": 8,
        "eden-ai": 55,
        "edge": "xai-api",
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        "weight": 7,
        "xai-api": 63
      }
    ],
    "summary": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments \u0026 pricing. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "eden-ai": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.",
      "xai-api": "Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api",
    "json": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.min.md"
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  "markdown": "xAI API (Grok) scores 71.7 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments \u0026 pricing. Both do llm inference.\n\n- Eden AI: grade C, 59.9/100, rank #675 of 1510. Markdown https://www.anchorterminal.com/tools/eden-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n- xAI API (Grok): grade BB, 71.7/100, rank #152 of 1510. Markdown https://www.anchorterminal.com/tools/xai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/xai-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Eden AI (C)\n\nGood for: Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.\n\nAhead on:\n- Payments \u0026 pricing, 30 against 20\n\nWatch for: No public status page, incident history or SLA found\n\n### xAI API (Grok) (BB)\n\nGood for: Agents that want a capable model at a low per-token price with built-in web and X search, remote MCP and voice, and teams that need self-serve ZDR or US-only processing.\n\nAhead on:\n- Reliability, 55 against 33\n- Schema \u0026 documentation, 88 against 81\n- Agent ergonomics, 90 against 75\n- Security \u0026 auth, 97 against 82\n- Maintenance \u0026 community, 77 against 58\n- Transparency \u0026 trust, 63 against 55\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: API models outage of about 3 hours 40 minutes on 3 September 2026, and high error rates on grok-4.6 and grok-4.5 on 17 August\n\n\n## Why the edge\n\n### Reliability: xAI API (Grok) +22\n\n- Eden AI (33): Router, read on the hosted lines. No status page is linked from the site or docs, and status.edenai.co didn't resolve for us on 6 November 2026 (0). No incident history to read (5). The rate-limits page gives 10 requests a second per account, shared across keys, while the plans page gives 7 a second, raisable to 15, so the figure is documented but inconsistent (10). Fallback retries the next model or provider on a 429 or error inside one request, but no client-facing 429 or Retry-After guidance was found (8). No SLA published; 'Dedicated support \u0026 SLA' is listed only for the custom Advanced plan, and the pricing page's '99.99%' uptime is a claim without a status page behind it (0). The v3 API is GA (10). 0+5+10+8+0+10 = 33.\n- xAI API (Grok) (55): Status page at status.x.ai with components for the global and US API endpoints, voice, the consumer apps and, since the Cursor merger, Cursor's services, with an RSS feed (20). The feed, read on 6 November, now holds 267 incidents back to 11 August, so the whole 90-day window is readable. On the API components there were high error rates on grok-4.6 and grok-4.5 from 21:57 to 23:28 UTC on 17 August (about 90 minutes) and a models outage on the global and US endpoints from 13:30 to 17:09 UTC on 3 September (about 3 hours 40 minutes), so several majors. A 26-minute datacenter outage across the API on 22 September, voice disruptions of 12 and 28 minutes on 10 September and 6 October, a 63-minute voice and Imagine degradation on 30 October and a 37-second model degradation on 24 October add to the record (0). Rate limits published per model and tier, grok-4.7 at Tier 0 is 150 requests a second and 50M TPM, with the per-second cap derived as RPM divided by 48 (15). The rate-limits page shows exponential backoff on 429, but no Retry-After header or overload guidance was found (10 of 15). No SLA found in the docs or llms.txt (0). The Responses API has been GA since September 2025 and grok-4.7 carries no preview label (10).\n\n### Maintenance \u0026 community: xAI API (Grok) +19\n\n- Eden AI (58): Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.\n- xAI API (Grok) (77): Model reading. grok-imagine-image-quality and grok-imagine-image-pro retired on 2 November 2026 as announced in September, Grok Voice 3.0 and custom moderation controls in October, Grok 4.7 on 21 September (30). No minimum notice period found. Retirements come as dated migration guides, retired slugs redirect to a replacement rather than failing, billed at the replacement's price, and grok-voice-2.0 was deprecated in October with no end date (4 of 12). Shutdowns in the last 90 days with dates given in advance, `grok-voice-transcribe-1.0` on 2 October and `grok-imagine-image-quality` on 2 November (8 of 8). Release notes several times a month but dated only by month, support by email and a Discord #help channel, not tested. On xai-sdk-python a collaborator commented on 2 of the 16 most recent threads with replies, and most outside pull requests since 23 October are open without a maintainer reply (10 of 15, down from 12). The repository has CI, release and version-bump workflows (5 of 10). One current first-party SDK, `xai-sdk` 1.21.0 tagged on 23 October, Python only (10 of 15). Supported runtimes stated, Python 3.10 or later (10).\n\n### Agent ergonomics: xAI API (Grok) +15\n\n- Eden AI (75): Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.\n- xAI API (Grok) (90): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling with parallel calls on by default and `tool_choice` of auto, required, none or a named function (20). Guaranteed structured outputs (15). Automatic prompt caching, cached input at 0.25x on grok-4.7 ($0.50 per million) and 0.16x on grok-4.3 (15). 500,000-token context on grok-4.7 and 1,000,000 on grok-4.3, 13 of 15 for the default model's 500K. The Batch API is now 20% off on grok-4.7, 4.6 and 4.5 as well as the older models, with batch requests outside the rate limits (10 of 10, up from 5 on 6 October). One first-party SDK, `xai-sdk` for Python, with the OpenAI SDKs and Vercel's AI SDK documented as alternatives (5 of 10). Status codes documented with fixes, no Retry-After header found (12 of 15).\n\n### Security \u0026 auth: xAI API (Grok) +15\n\n- Eden AI (82): Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.\n- xAI API (Grok) (97): Model reading. Team API keys with ACLs per endpoint and per model, QPM and TPM caps, expiry, and create, rotate, disable and delete through the Management API, plus documented mTLS. GitHub secret scanning disables leaked keys and emails the owner (30). The security FAQ says SpaceXSI never trains on API inputs or outputs without explicit permission (20). Requests and responses are kept 30 days for abuse auditing, then deleted, and team admins can switch on zero data retention themselves, confirmed by an `x-zero-data-retention` header on every response (15). Console audit log and a Management API audit-events endpoint, plus optional per-key request logging (15). security.txt valid to 2027-06-29 with a HackerOne bug bounty and a separate safety contact for prompt-injection issues. SOC 2 Type 2 is claimed in the security FAQ with the reports behind an NDA in the trust centre, so 17 of 20. Remote MCP doesn't support `require_approval`, which the model checklist doesn't score but reviewers should see. New in October, a `guidelines` array lets the caller make the model decline nsfw, violence or profanity content, which the checklist doesn't score.\n\n### Payments \u0026 pricing: Eden AI +10\n\n- Eden AI (30): No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.\n- xAI API (Grok) (20): No x402, MPP or L402 (0). Per-token and per-call prices published without a login on docs.x.ai/developers/pricing (20). No free tier found for the text API, and the quickstart says to load the account with credits (0). Sign-up is in the browser at console.x.ai. The Management API can create keys and top up prepaid credit, but only with a management key made by a person in the console, so no line credit (0).\n\n### Transparency \u0026 trust: xAI API (Grok) +8\n\n- Eden AI (55): Editorial half only. Closed service under terms last updated 22 October 2026, naming Eden AI SAS and French law with courts in Lyon (15). The data retention page, terms and DPA agree that content isn't stored by default, and the docs carry a per-provider table of training, retention and ZDR (27). No deprecation policy found; models are dropped in docs updates without dated notice that we found (5). The DPA's Annex 2 names operational subprocessors (AWS EMEA, ClickHouse, Sentry, Metabase, Stripe, Brevo and others) with their roles, and the EU endpoint keeps routing in the EU (18). 15+27+5+18 = 65.\n- xAI API (Grok) (63): Closed service under xAI's enterprise terms, with the Python SDK under Apache-2.0 (15). The docs agree with each other on no training, 30-day abuse retention, 30-day storage of stateful responses and the ZDR route, but the privacy policy, enterprise terms and DPA at x.ai/legal answered a Cloudflare block page on 6 October and again on 6 November, so they couldn't be compared (15 of 30). Dated migration guides and redirect tables for each retirement, but no written deprecation policy, and Chat Completions, Anthropic compatibility and grok-voice-2.0 are labelled deprecated with no date (12 of 20). The US regional endpoint states what stays in the US, the global endpoint guarantees no region, and no subprocessor list was readable (10 of 20).\n\n## Score by category\n\n| Category | Weight | Eden AI | xAI API (Grok) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 33 | 55 | xAI API (Grok) +22 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 81 | 88 | xAI API (Grok) +7 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 90 | xAI API (Grok) +15 |\n| Security \u0026 auth | 14% (17.5 this run) | 82 | 97 | xAI API (Grok) +15 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 20 | Eden AI +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 58 | 77 | xAI API (Grok) +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 63 | xAI API (Grok) +8 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.9 · C** | **71.7 · BB** | |\n\n## Facts side by side\n\n| Fact | Eden AI | xAI API (Grok) |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Eden AI SAS | SpaceXSI (xAI) |\n| Hosted endpoint | `https://mcp.edenai.run/mcp` | `https://api.x.ai/v1` |\n| Transports | HTTP, Streamable HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Proprietary service under xAI's enterprise terms of service. The Python SDK is Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-05 | 2026-11-02 |\n| Terms last updated | 2026-10-22 | 2026-10-27 |\n| Privacy policy last updated | 2026-10-22 | 2026-10-27 |\n| Customer content may train models | not found in the text | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | none | 597 stars, 912k PyPI/wk |\n\n## Verdicts\n\n**Eden AI.** Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.\n\n**xAI API (Grok).** Grok 4.7 at $2/$6 per million tokens, now 20% off in batch, with a public OpenAPI spec, llms.txt, API keys limited by endpoint and model, and self-serve zero data retention. The API endpoints had a 3 hour 40 minute models outage on 3 September 2026, no SLA was found, and there's no free tier or first-party SDK beyond Python.\n\n## Before you call either\n\n### Eden AI\n\n1. Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them\n2. Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed\n3. Set max_tokens to 500 or more for reasoning models, or the answer can come back empty\n4. Pass a fallbacks list so a provider 429 or error retries inside one request\n5. Poll check_job for MCP tools marked long-running instead of calling them again\n\n### xAI API (Grok)\n\n1. Build on the Responses API at https://api.x.ai/v1. Chat Completions is labelled deprecated and the Anthropic-compatible endpoint fully deprecated\n2. Pin a dated model slug. A retired slug keeps answering from a replacement model, billed at the replacement's price\n3. Back off exponentially on 429. The per-second cap is the per-minute budget divided by 48, with a minimum of 2\n4. Set `allowed_tools` on remote MCP servers. There's no approval step, and every exposed tool enters the context\n5. Use https://us.api.x.ai/v1 when processing must stay in the US. It costs 1.1x and serves only grok-4.7 and grok-4.6\n\n## Questions\n\n### Which is better for AI agents, Eden AI or xAI API (Grok)?\n\nxAI API (Grok) scores 71.7 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments \u0026 pricing.\n\n### Do Eden AI and xAI API (Grok) need an API key?\n\nBoth need an API key.\n\n### Can an agent call Eden AI and xAI API (Grok) without installing anything?\n\nYes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and xAI API (Grok) at https://api.x.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"eden-ai\", \"b\": \"xai-api\"}`. From a terminal: `anchor compare eden-ai xai-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/eden-ai.json and https://www.anchorterminal.com/api/v1/tools/xai-api.json\n\n## Other comparisons with Eden AI or xAI API (Grok)\n\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs xAI API (Grok)](https://www.anchorterminal.com/compare/amazon-bedrock-vs-xai-api.md)\n- [Claude API vs Eden AI](https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md)\n- [Claude API vs xAI API (Grok)](https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.md)\n- [Antseed vs xAI API (Grok)](https://www.anchorterminal.com/compare/antseed-vs-xai-api.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [Azure OpenAI in Foundry Models vs xAI API (Grok)](https://www.anchorterminal.com/compare/azure-openai-vs-xai-api.md)\n- [BlockRun.AI vs 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