{ "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": 672, "ranked": true, "rankOf": 1486, "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": "2026-11-07T18:20:22.496540152Z", "lastOk": true, "lastStatus": 405, "lastMs": 123, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 50, "p95ms24h": 129, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "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": "2026-11-07T18:20:22.496540152Z" } }, "answer": "OpenAI API scores 83.9 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.", "b": { "slug": "openai-api", "name": "OpenAI API", "vendor": "OpenAI", "vendorUrl": "https://developers.openai.com", "kind": "model", "category": "inference", "summary": "OpenAI's API for accessing its models through Responses, Chat Completions and Batch endpoints.", "url": "https://www.anchorterminal.com/tools/openai-api", "markdownUrl": "https://www.anchorterminal.com/tools/openai-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/openai-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/openai-api.json", "dns": "openai-api.grade.anchorterminal.com", "repo": "https://github.com/openai/openai-python", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://api.openai.com/v1", "packages": [ { "registry": "pypi", "name": "openai", "main": true }, { "registry": "npm", "name": "openai", "main": true } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` with a project key. Some models and tools need business or ID verification first.", "pricing": "usage", "pricingNotes": "Prepaid credit, with the Build tier reached at $5 in credit purchases, Launch at $100 and Grow at $500. Long context over 272K tokens costs 2x input and 1.5x output. Cache reads 0.1x input (0.05x on GPT-6.1 Sol and GPT-6.1 Terra), cache writes 1.25x from GPT-5.6 on, or 2.5x for the 12-hour lifetime in the Responses API since 20 October. Batch and Flex half price, Fast mode 2x, Ultrafast 6x (GPT-6 Astra, and GPT-6.1 Sol since 8 October). Data residency endpoints add 10% for models released on or after 5 March 2026, and FedRAMP endpoints add 10% from 1 November 2026. Web search $10 per 1,000 calls plus search content tokens, file search $2.50 per 1,000, hosted containers from $0.03 per 20-minute session (https://developers.openai.com/api/docs/pricing).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Access needs an account with prepaid credit.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 31300, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://developers.openai.com/api/docs", "rateLimitsUrl": "https://developers.openai.com/api/docs/guides/rate-limits", "llmsTxt": "https://developers.openai.com/llms.txt", "openapi": "https://github.com/openai/openai-openapi", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "card-required", "openapi", "llms-txt" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 83.9, "grade": "A", "agentReady": true, "rank": 6, "ranked": true, "rankOf": 1486, "categoryRank": 2, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 98, "maintenance": 87, "payments": 30, "reliability": 75, "schema": 100, "security": 100, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.", "bestFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.", "strengths": [ "Official OpenAPI document and an llms.txt index", "Project keys can be restricted per endpoint to None, Read or Write, and mutual TLS workload identity is GA", "A dated deprecations page, and `GET /v1/models` returns each model's `shutdown_date`", "GPT-6 Luna at $0.10/$0.50 per million tokens with the same 1.05M context as Astra", "Scale Tier comes with a 99.9% uptime SLA" ], "weaknesses": [ "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026", "Heavy migration calendar. Assistants API gone on 2026-08-26, Agent Builder, Evals and `v1/prompts` on 2026-11-30, GPT-5 and o3 on 2026-12-11", "GPT-6 models aren't available on the Free tier, so a card and prepaid credit come first in practice", "GPT-6 Astra has no custom temperature, no logprobs and no tool calling outside the Responses API", "GPT-4o and GPT-4.1 snapshots got 92 days' notice on 14 October, against the 6 months the deprecations page promises GA models" ], "agentNotes": [ "Build on the Responses API. Astra calls tools only there", "Use `gpt-6-luna` for routing and extraction, `gpt-6.1-terra` for screens, images and computer use at half Sol's price, and `gpt-6.1-sol` for most work. The models page still points unsure callers to `gpt-6-astra`", "Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the `gpt-5`, `o3` and related snapshots before 2026-12-11, and `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01. 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"promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gpt-6-sol": { "openrouterId": "openai/gpt-6-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-10-04T21:56:15.872733218Z" }, "gpt-6.1-sol": { "openrouterId": "openai/gpt-6.1-sol", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gpt-6.1-terra": { "openrouterId": "openai/gpt-6.1-terra", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1050000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" } }, "github": { "repo": "openai/openai-python", "checkedAt": "2026-11-02T09:13:10.459648475Z", "stars": 32015, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T03:47:02Z", "openIssues": 40, "openPRs": 54, "issuesOpened90d": 42, "issuesClosed90d": 220, "prsMerged90d": 437, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-11-02T03:19:31Z" }, "replies": { "sampled": 25, "unanswered": 9, "medianDays": 3.6 } }, "updatedAt": "2026-11-07T18:21:36.727476942Z" } }, "edges": [ { "by": 42, "category": "reliability", "leads": "openai-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.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75." }, "scores": { "a": 33, "b": 75 } }, { "by": 35, "category": "transparency", "leads": "openai-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 with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and `GET /v1/models` returns each model's `shutdown_date` (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20)." }, "scores": { "a": 55, "b": 90 } }, { "by": 29, "category": "maintenance", "leads": "openai-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. GPT-6 Rosalind, a life-sciences model for approved organisations, launched on 30 October, after GPT-6.1 Terra on 26 October and the Decisions API GA on 22 October (30). Published minimum notice of 6 months for GA models, 3 months for specialised variants, as little as 2 weeks for previews. On 14 October GPT-4o (`gpt-4o-2024-08-06`, `gpt-4o-2024-11-20`), GPT-4o mini, GPT-4.1 and GPT-4.1 mini were given a shutdown date of 14 January 2027, 92 days, with no safety or compliance reason stated. These are GA models, so the page's own 6-month minimum wasn't kept, as with `gpt-5.4-cyber`'s 20 days in September. 8 of 12, the award for a minimum of two to three months in practice. Five shutdown dates in the 90 days to 1 November, the Assistants API on 26 August (announced in August 2025), `gpt-5.2-chat-latest` and `gpt-5.3-chat-latest` on 10 August (announced 8 May), `gpt-3.5-turbo-instruct`, `babbage-002`, `davinci-002` and `gpt-3.5-turbo-1106` on 28 September (announced 26 September 2025, missed in the 27 October count), `gpt-5.4-cyber` on 1 October and the legacy snapshots on 23 October (announced 22 April). Sora 2 and the Videos API (24 September) are scored on the openai-sora listing. Four of the five kept the published notice, so 4 of 8 as before, as amazon-bedrock has for four dates after full notice. Dated changelog several times a month and a help centre (15 of 15). openai-python had 215 open issues per the 1 October check, replies not sampled (5 of 10). Current official SDKs, `openai` 3.42.0 on PyPI (31 October) and npm `openai` 7.47.0 (15). Supported runtimes stated, Python 3.10 or later and Node 22 or later, the npm package's `engines` re-read on 1 November (10)." }, "scores": { "a": 58, "b": 87 } }, { "by": 23, "category": "ergonomics", "leads": "openai-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). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15)." }, "scores": { "a": 75, "b": 98 } }, { "by": 19, "category": "schema", "leads": "openai-api", "name": "Schema \u0026 documentation", "reasons": { "a": "Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.", "b": "Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15)." }, "scores": { "a": 81, "b": 100 } }, { "by": 18, "category": "security", "leads": "openai-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. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; `/v1/agents`, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20)." }, "scores": { "a": 82, "b": 100 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Eden AI SAS", "b": "OpenAI", "name": "Vendor" }, { "a": "https://mcp.edenai.run/mcp", "b": "https://api.openai.com/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": "Apache-2.0 (SDKs)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-05", "b": "2026-10-30", "name": "Last release" }, { "a": "2026-10-22", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "2026-10-22", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "31k stars", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (8)", "name": "Agent reviews" } ], "faq": [ { "answer": "OpenAI API scores 83.9 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Eden AI or OpenAI API?" }, { "answer": "Both need an API key.", "question": "Do Eden AI and OpenAI API need an API key?" }, { "answer": "Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and OpenAI API at https://api.openai.com/v1.", "question": "Can an agent call Eden AI and OpenAI API without installing anything?" } ], "goodFor": [ { "aheadOn": null, "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, 75 against 33", "Schema \u0026 documentation, 100 against 81", "Agent ergonomics, 98 against 75", "Security \u0026 auth, 100 against 82", "Maintenance \u0026 community, 87 against 58", "Transparency \u0026 trust, 90 against 55" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.", "slug": "openai-api", "watchFor": "Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026" } ], "history": { "eden-ai": null, "openai-api": [ { "causes": [ "correction" ], "date": "2026-11-01", "delta": 1, "from": 82.9, "fromGrade": "A", "to": 83.9, "toGrade": "A" }, { "causes": [ "product" ], "date": "2026-10-17", "delta": -0.4, "from": 83.3, "fromGrade": "A", "to": 82.9, "toGrade": "A" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.2, "from": 83.5, "fromGrade": "A", "to": 83.3, "toGrade": "A" } ] }, "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-openai-api.json", "title": "Amazon Bedrock vs OpenAI API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-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-openai-api.json", "title": "Claude API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-openai-api.json", "title": "Antseed vs OpenAI API", "url": "https://www.anchorterminal.com/compare/antseed-vs-openai-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-openai-api.json", "title": "Azure OpenAI in Foundry Models vs OpenAI API", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-openai-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-openai-api.json", "title": "BlockRun.AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-openai-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-openai-api.json", "title": "Cerebras Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-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-openai-api.json", "title": "Cloudflare AI Gateway vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-openai-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-openai-api.json", "title": "Cloudflare Workers AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-openai-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-openai-api.json", "title": "Cohere Chat API (Command models) vs OpenAI API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-openai-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-openai-api.json", "title": "DeepInfra vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-openai-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-openai-api.json", "title": "DeepSeek API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-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" }, { "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-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/eden-ai-vs-xai-api.json", "title": "Eden AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-openai-api.json", "title": "Glimpse vs OpenAI API", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api.json", "title": "Fireworks AI Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api.json", "title": "Gemini Developer API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-openai-api.json", "title": "GroqCloud vs OpenAI API", "url": "https://www.anchorterminal.com/compare/groq-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api.json", "title": "Hugging Face Inference Providers vs OpenAI API", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openai-api.json", "title": "Inkling 2 Small vs OpenAI API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api.json", "title": "Jais 3 vs OpenAI API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json", "title": "Meta Model API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api.json", "title": "MiniMax API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api.json", "title": "Mistral AI API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.json", "title": "Muse Spark Open vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-openai-api.json", "title": "Nemotron 3.5 Super VL vs OpenAI API", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api.json", "title": "Novita AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter.json", "title": "OpenAI API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/openai-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference.json", "title": "OpenAI API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-ramp-router.json", "title": "OpenAI API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.json", "title": "OpenAI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-routerplus.json", "title": "OpenAI API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/openai-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova.json", "title": "OpenAI API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json", "title": "OpenAI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-simplismart.json", "title": "OpenAI API vs Simplismart", "url": "https://www.anchorterminal.com/compare/openai-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api.json", "title": "OpenAI API vs StepFun API", "url": "https://www.anchorterminal.com/compare/openai-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-swe-2-flash.json", "title": "OpenAI API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/openai-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub.json", "title": "OpenAI API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference.json", "title": "OpenAI API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/openai-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway.json", "title": "OpenAI API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai.json", "title": "OpenAI API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/openai-api-vs-vertex-ai" }, { "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/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" } ], "panel": null, "scores": [ { "by": 42, "eden-ai": 33, "edge": "openai-api", "key": "reliability", "name": "Reliability", "openai-api": 75, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 19, "eden-ai": 81, "edge": "openai-api", "key": "schema", "name": "Schema \u0026 documentation", "openai-api": 100, "weight": 13 }, { "by": 23, "eden-ai": 75, "edge": "openai-api", "key": "ergonomics", "name": "Agent ergonomics", "openai-api": 98, "weight": 13 }, { "by": 18, "eden-ai": 82, "edge": "openai-api", "key": "security", "name": "Security \u0026 auth", "openai-api": 100, "weight": 14 }, { "by": 0, "eden-ai": 30, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "openai-api": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 29, "eden-ai": 58, "edge": "openai-api", "key": "maintenance", "name": "Maintenance \u0026 community", "openai-api": 87, "weight": 7 }, { "by": 35, "eden-ai": 55, "edge": "openai-api", "key": "transparency", "name": "Transparency \u0026 trust", "openai-api": 90, "weight": 7 } ], "summary": "OpenAI API scores 83.9 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. 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.", "openai-api": "Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api", "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.min.md" }, "markdown": "OpenAI API scores 83.9 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Eden AI: grade C, 59.9/100, rank #672 of 1486. Markdown https://www.anchorterminal.com/tools/eden-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n- OpenAI API: grade A, 83.9/100, rank #6 of 1486. Markdown https://www.anchorterminal.com/tools/openai-api.md · JSON https://www.anchorterminal.com/api/v1/tools/openai-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\nWatch for: No public status page, incident history or SLA found\n\n### OpenAI API (A)\n\nGood for: Agents that want one vendor for text, images, audio, hosted tools and remote MCP, with strict schemas and fine-grained keys, and four GPT-6 price points from Luna to Astra.\n\nAhead on:\n- Reliability, 75 against 33\n- Schema \u0026 documentation, 100 against 81\n- Agent ergonomics, 98 against 75\n- Security \u0026 auth, 100 against 82\n- Maintenance \u0026 community, 87 against 58\n- Transparency \u0026 trust, 90 against 55\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026\n\n\n## Why the edge\n\n### Reliability: OpenAI API +42\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- OpenAI API (75): Status page at status.openai.com with component history (20). Two API-wide majors in the 90 days to 1 November, elevated errors across ChatGPT, Codex and the API (the Agents API included) on 29 September, with Chat Completions, Responses, Batch, Realtime, Embeddings, Images, Files and the other API components degraded from 17:52 to 23:14 UTC, and elevated error rates across API models on 17 September, with eleven components degraded from 20:20 to 21:20 UTC. Two majors give 5 of 30. The 25 July incident is now outside the window. The 29 September write-up, posted on 6 October, traces it to a feature rollout that exhausted shared network connection capacity. Every other incident since 3 August that lists an API component is partial or under an hour, so minor. Degraded performance across ChatGPT, Codex and the APIs on 21 October listed every API component but ran 22 minutes (02:26 to 02:48 UTC). Single-model incidents were GPT-5.6 Sol errors on 11 September (09:08 to 11:21 UTC), `gpt-5.6-luna` errors on 21 October (70 minutes) and GPT-6.1 Sol degraded performance on Batch, Chat Completions and Responses on 27 October (78 minutes). Partial incidents were latency for some Responses requests on the US endpoint on 31 August and 1 September, image generation where some requests failed on 8 September, latency for some Responses and Chat Completions requests on 30 September, large-PDF errors in Responses and an Agents API computer use incident on 6 October, Responses errors for users in India, Japan and Korea on 22 October and errors on some GPT Image 2 edit requests on 30 October (14:35 to 18:36 UTC). Image model incidents on 16 September and 14 October and file download errors on 19 October each ran about 40 minutes. FedRAMP errors for Astra and Sol on 21 October and authentication errors near Illinois on 20 October list no API component. Rate limits published per tier and model family with rate-limit headers (15). 429 guidance, re-read on 1 November, covers `Retry-After` as a minimum wait, backoff with jitter when it's missing, a gradual ramp, and splits `slow_down` (429) from `server_is_overloaded` (503) (15). Scale Tier carries a 99.9% uptime SLA, through sales, per the 1 October check, not re-read on 1 November (10). Responses and Chat Completions are GA (10). 20 + 5 + 15 + 15 + 10 + 10 = 75.\n\n### Transparency \u0026 trust: OpenAI API +35\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- OpenAI API (90): Closed service with clear terms, SDKs Apache-2.0 (15). The data-controls guide, re-read on 1 November, gives retention periods per endpoint, the training default and the ZDR route. The DPA, effective 1 January 2026, commits to return or deletion of customer data on termination, 30 days to object to a new subprocessor, and SCCs with the UK Addendum for transfers, and nothing in it conflicts with the guide, per the 4 October check, not re-read on 1 November (30). Deprecations page with announcement and shutdown dates, and `GET /v1/models` returns each model's `shutdown_date` (20). The subprocessor list, updated 9 July 2026, names its third-party subprocessors and OpenAI affiliates with the processing countries for each and a form to get notice of new ones, and data residency regions are listed, per the 4 October check, not re-read on 1 November (20).\n\n### Maintenance \u0026 community: OpenAI API +29\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- OpenAI API (87): Model reading. GPT-6 Rosalind, a life-sciences model for approved organisations, launched on 30 October, after GPT-6.1 Terra on 26 October and the Decisions API GA on 22 October (30). Published minimum notice of 6 months for GA models, 3 months for specialised variants, as little as 2 weeks for previews. On 14 October GPT-4o (`gpt-4o-2024-08-06`, `gpt-4o-2024-11-20`), GPT-4o mini, GPT-4.1 and GPT-4.1 mini were given a shutdown date of 14 January 2027, 92 days, with no safety or compliance reason stated. These are GA models, so the page's own 6-month minimum wasn't kept, as with `gpt-5.4-cyber`'s 20 days in September. 8 of 12, the award for a minimum of two to three months in practice. Five shutdown dates in the 90 days to 1 November, the Assistants API on 26 August (announced in August 2025), `gpt-5.2-chat-latest` and `gpt-5.3-chat-latest` on 10 August (announced 8 May), `gpt-3.5-turbo-instruct`, `babbage-002`, `davinci-002` and `gpt-3.5-turbo-1106` on 28 September (announced 26 September 2025, missed in the 27 October count), `gpt-5.4-cyber` on 1 October and the legacy snapshots on 23 October (announced 22 April). Sora 2 and the Videos API (24 September) are scored on the openai-sora listing. Four of the five kept the published notice, so 4 of 8 as before, as amazon-bedrock has for four dates after full notice. Dated changelog several times a month and a help centre (15 of 15). openai-python had 215 open issues per the 1 October check, replies not sampled (5 of 10). Current official SDKs, `openai` 3.42.0 on PyPI (31 October) and npm `openai` 7.47.0 (15). Supported runtimes stated, Python 3.10 or later and Node 22 or later, the npm package's `engines` re-read on 1 November (10).\n\n### Agent ergonomics: OpenAI API +23\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- OpenAI API (98): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and forced tool choice, 18 of 20 because GPT-6 Astra, GPT-6.1 Sol and GPT-6.1 Terra call tools only through the Responses API (18). Strict structured outputs (15). Automatic prompt caching with cached input at 0.1x on Astra and Luna ($0.01 per million on Luna) and 0.05x on GPT-6.1 Sol ($0.10) and GPT-6.1 Terra ($0.05), and a 12-hour cache lifetime in the Responses API since 20 October (15). 1.05M context on Astra, GPT-6.1 Sol, GPT-6.1 Terra and Luna (15). Batch at half price (10). Official SDKs in Python, JavaScript and more (10). Documented error codes with retry guidance (15).\n\n### Schema \u0026 documentation: OpenAI API +19\n\n- Eden AI (81): Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.\n- OpenAI API (100): Official OpenAPI document (openapi.yaml and openapi.json) in the openai/openai-openapi repository, whose openapi.yaml (version 2.3.0, updated 31 October) lists `gpt-6.1-terra` (25). llms.txt index with per-product files, and every docs page has a Markdown twin at `.md` (10). The reference documents each parameter, and model pages say which model fits which job (20). Structured outputs with `strict: true` on schemas and function tools (15). Error codes guide with types and recovery advice, now with a 400 `service_tier` error for tiers a project doesn't allow (15). Dated model snapshots and a dated changelog, last entry 30 October (15).\n\n### Security \u0026 auth: OpenAI API +18\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- OpenAI API (100): Model reading. Project keys with All, Restricted (per-endpoint None, Read or Write) and Read Only permissions, service accounts, and mutual TLS with X.509 workload identity GA since 26 August, per the 1 October check. The changelog adds project key expiry dates on 10 September, key-creation controls on 15 September and, on 21 October, organisation and project settings that limit which service tiers a project may use (30). API data not used for training unless the customer opts in, since 1 March 2023 (20). Abuse-monitoring logs kept up to 30 days, and Zero Data Retention or Modified Abuse Monitoring by approval. The data-controls guide re-read on 1 November lists Chat Completions, Responses, Decisions and ten other endpoints as ZDR-eligible; `/v1/agents`, Conversations, Files and vector stores aren't (15). Usage and Costs filter by API key since 4 August, with Admin APIs to match, and audit logs for enterprise (15). SOC 2 Type 2, ISO 27001, 27017, 27018, 27701 and 42001 per the 1 October check, not re-read on 1 November, a Bugcrowd bug bounty and a coordinated disclosure policy, both linked from a signed security.txt. That security.txt had no Expires field on 27 October, which RFC 9116 requires, so the disclosure policy carries this line. It wasn't re-read on 1 November (20).\n\n## Score by category\n\n| Category | Weight | Eden AI | OpenAI API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 33 | 75 | OpenAI API +42 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 81 | 100 | OpenAI API +19 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 98 | OpenAI API +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 82 | 100 | OpenAI API +18 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 30 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 58 | 87 | OpenAI API +29 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 90 | OpenAI API +35 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.9 · C** | **83.9 · A** | |\n\n## Facts side by side\n\n| Fact | Eden AI | OpenAI API |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Eden AI SAS | OpenAI |\n| Hosted endpoint | `https://mcp.edenai.run/mcp` | `https://api.openai.com/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 | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-05 | 2026-10-30 |\n| Terms last updated | 2026-10-22 | couldn't be read |\n| Privacy policy last updated | 2026-10-22 | couldn't be read |\n| Customer content may train models | not found in the text | couldn't be read |\n| Terms restrict automated access | not found in the text | couldn't be read |\n| Terms restrict benchmarking | not found in the text | couldn't be read |\n| Terms or service can change without notice | not found in the text | couldn't be read |\n| Arbitration or class-action waiver | not found in the text | couldn't be read |\n| Popularity | none | 31k stars |\n| Agent reviews | none | 3.5/5 (8) |\n\n## How the scores have moved\n\n### Eden AI\n\nNo score change since it was listed.\n\n### OpenAI API\n\n- +1.0 on 1 November 2026: correction\n- -0.4 on 17 October 2026: product\n- -0.2 on 8 October 2026: checklist\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**OpenAI API.** Official OpenAPI document and an llms.txt index. Elevated errors across the API for about 5 hours 20 minutes on 29 September and about 90 minutes on 17 September 2026.\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### OpenAI API\n\n1. Build on the Responses API. Astra calls tools only there\n2. Use `gpt-6-luna` for routing and extraction, `gpt-6.1-terra` for screens, images and computer use at half Sol's price, and `gpt-6.1-sol` for most work. The models page still points unsure callers to `gpt-6-astra`\n3. Move off the GPT-4o and GPT-4.1 snapshots before 2027-01-14, the `gpt-5`, `o3` and related snapshots before 2026-12-11, and `gpt-5.1`, `gpt-5.3-codex` and `gpt-5.4-nano` before 2027-04-01. Check `shutdown_date` on `GET /v1/models`\n4. Treat 429 `slow_down` as a ramp limit and 503 `server_is_overloaded` as a retry, and follow `Retry-After` when it's sent\n5. Prompts over 272K tokens cost double on input. Trim before you pay for it\n\n## Questions\n\n### Which is better for AI agents, Eden AI or OpenAI API?\n\nOpenAI API scores 83.9 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.\n\n### Do Eden AI and OpenAI API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Eden AI and OpenAI API without installing anything?\n\nYes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and OpenAI API at https://api.openai.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"eden-ai\", \"b\": \"openai-api\"}`. From a terminal: `anchor compare eden-ai openai-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/eden-ai.json and https://www.anchorterminal.com/api/v1/tools/openai-api.json\n\n## Other comparisons with Eden AI or OpenAI API\n\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs OpenAI API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-openai-api.md)\n- [Claude API vs Eden AI](https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md)\n- [Claude API vs OpenAI API](https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.md)\n- [Antseed vs OpenAI API](https://www.anchorterminal.com/compare/antseed-vs-openai-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 OpenAI API](https://www.anchorterminal.com/compare/azure-openai-vs-openai-api.md)\n- [BlockRun.AI vs 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[Eden AI vs LiteLLM](https://www.anchorterminal.com/compare/eden-ai-vs-litellm.md)\n- [Eden AI vs OpenRouter](https://www.anchorterminal.com/compare/eden-ai-vs-openrouter.md)\n- [Eden AI vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router.md)\n- [Eden AI vs RouterPlus](https://www.anchorterminal.com/compare/eden-ai-vs-routerplus.md)\n- [Eden AI vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub.md)\n- [Eden AI vs Vercel AI Gateway](https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", 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