{ "data": { "a": { "slug": "eden-ai", "name": "Eden AI", "vendor": "Eden AI SAS", "vendorUrl": "https://www.edenai.co", "kind": "router", "category": "inference", "summary": "Eden AI is a French AI gateway with one OpenAI-compatible API key for about 1,000 chat and expert models from 80 or more providers, including OCR, speech, translation and image analysis, with an EU-only endpoint and a hosted MCP server.", "url": "https://www.anchorterminal.com/tools/eden-ai", "markdownUrl": "https://www.anchorterminal.com/tools/eden-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/eden-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/eden-ai.json", "dns": "eden-ai.grade.anchorterminal.com", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://mcp.edenai.run/mcp", "packages": [], "auth": "api-key", "authNotes": "Bearer key created in the dashboard at app.edenai.run after a browser signup. Keys carry budgets, expiry and attribution, can be managed through a key API, and can be limited to chosen models by deny-by-default guardrails. The MCP server takes the same key in the Authorization header.", "pricing": "usage", "pricingNotes": "Provider list prices with no markup plus a 5.5% platform fee applied when buying credits. Prepaid credits through Stripe by card, PayPal or bank transfer, with optional auto-refill. Some models are billed $0 for tests. The Advanced plan is by quote.", "priceSummary": "5.5% fee", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in llms.txt, the OpenAPI spec, the pricing pages or the agent catalogue (checked 2026-11-06). Credits are bought through Stripe.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://www.edenai.co/docs", "llmsTxt": "https://www.edenai.co/llms.txt", "openapi": "https://api.edenai.run/v3/docs/openapi.json", "capabilities": [ "inference.router", "inference.llm", "embed.text", "translate.text", "translate.documents", "docs.ocr", "speech.stt", "speech.tts", "image.generate", "guard.moderation" ], "tags": [ "hosted", "router", "openai-compatible", "usage-priced", "prepaid", "mcp", "remote-mcp", "api-key", "llms-txt", "openapi", "eu", "eu-region", "soc2", "iso27001", "batch", "closed-source" ], "lastRelease": "2026-11-05", "graded": true, "anchor": { "graded": true, "score": 59.9, "grade": "C", "agentReady": false, "rank": 675, "ranked": true, "rankOf": 1510, "categoryRank": 22, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 58, "payments": 30, "reliability": 33, "schema": 81, "security": 82, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.", "bestFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.", "strengths": [ "OpenAI-compatible v3 API with an OpenAPI 3.1 spec and a keyless model catalogue with prices and regions", "EU endpoint that refuses models not cleared for European processing with HTTP 451", "Content isn't stored or used for training by default, with opt-in logs and enforceable Zero Data Retention", "Per-key budgets, expiry and deny-by-default guardrails, plus a key management API", "Hosted MCP server exposing OCR, speech, translation, web search and other expert models as tools" ], "weaknesses": [ "No public status page, incident history or SLA found", "The rate-limits page says 10 requests a second and the plans page says 7, raisable to 15", "No public changelog or deprecation policy", "The OpenAPI spec documents few error responses", "Credits are prepaid through Stripe with a 5.5% platform fee on every purchase" ], "agentNotes": [ "Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them", "Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed", "Set max_tokens to 500 or more for reasoning models, or the answer can come back empty", "Pass a fallbacks list so a provider 429 or error retries inside one request", "Poll check_job for MCP tools marked long-running instead of calling them again" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59.9 } ], "editorialScores": { "ergonomics": 75, "maintenance": 58, "payments": 30, "reliability": 33, "schema": 81, "security": 82, "transparency": 65 }, "provenanceScore": 44, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.edenai.run/v3/models", "claudeCode": "claude mcp add edenai --transport http https://mcp.edenai.run/mcp --header \"Authorization: Bearer $EDENAI_API_KEY\"", "config": { "mcpServers": { "edenai": { "headers": { "Authorization": "Bearer YOUR_EDENAI_API_KEY" }, "url": "https://mcp.edenai.run/mcp" } } } }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/eden-ai" }, "area": "models", "unitPrices": [ { "item": "Platform fee on credit purchases", "unit": "pct", "usd": 5.5, "note": "On top of provider list prices, which carry no markup" } ], "provenance": { "legalEntity": "Eden AI SAS", "domain": "edenai.co", "domainRegistered": "", "endpointOnVendorDomain": false, "terms": "https://www.edenai.co/terms", "privacy": "https://www.edenai.co/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The terms, last updated 22 October 2026, name Eden AI SAS, share capital €4,992, 19 rue Louis Guérin, 69100 Villeurbanne, France, under French law with courts in Lyon.", "The API and MCP server run on edenai.run, a second domain of the same company, while the site and docs are on edenai.co.", "robots.txt on www.edenai.co allows all agents and carries `Content-Signal: search=yes, ai-input=yes, ai-train=yes`.", "/.well-known/security.txt returns 404. No status page is linked, and status.edenai.co didn't resolve on 6 November 2026.", "RDAP for edenai.co wasn't read: rdap.org rate-limited us and the .co registry server wasn't tried." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/eden-ai.json", "live": { "slug": "eden-ai", "probe": { "target": "https://mcp.edenai.run/mcp", "method": "get", "lastAt": "2026-11-07T19:22:04.810042763Z", "lastOk": true, "lastStatus": 405, "lastMs": 58, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 50, "p95ms24h": 129, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "securityTxt": { "url": "https://edenai.co/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:41.694549385Z" }, "llmsTxt": { "url": "https://www.edenai.co/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:20.299431316Z" }, "pages": [ { "url": "https://www.edenai.co/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:28:13.706474894Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "21a1da47a2ce" }, { "url": "https://www.edenai.co/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:28:15.881335606Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "9cd0db8f0f61" } ], "mcpTools": { "url": "https://mcp.edenai.run/mcp", "checkedAt": "2026-11-07T01:44:01.27972989Z", "status": "ok", "protocol": "2025-11-25", "tools": [ { "name": "list_models", "description": "List available providers/models and their pricing.", "inputSchema": { "additionalProperties": false, "properties": { "tool": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Optional tool name (as returned by tools/list) to filter on." } }, "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "list_voices", "description": "List the voices a text-to-speech model accepts, for audio_tts's 'voice'.\n\nThe model's default voice comes first.", "inputSchema": { "additionalProperties": false, "properties": { "gender": { "anyOf": [ { "enum": [ "female", "male", "unknown" ], "type": "string" }, { "type": "null" } ], "default": null, "description": "Keep voices of this gender." }, "language": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Keep voices speaking this language: 'fr' matches every region,\n'fr-CA' only that locale. Multilingual voices are always kept." }, "limit": { "default": 50, "description": "Most voices to return (default 50, max 200); 'total' counts every match.", "type": "integer" }, "model": { "description": "The audio_tts model, as 'provider' or 'provider/model' (e.g. 'amazon/neural').", "type": "string" } }, "required": [ "model" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "upload_file", "description": "Upload a file to Eden AI and get a file ID to use in other tools.\n\nOnly needed for local file content. If you already have a public URL\nfor the file, pass that URL directly to the tool's file parameter\ninstead — no upload needed.", "inputSchema": { "additionalProperties": false, "properties": { "content_base64": { "description": "The file content, base64-encoded.", "type": "string" }, "expires_in_days": { "default": 30, "description": "How long Eden AI keeps the file (1-30, default 30).", "type": "integer" }, "filename": { "description": "Name with extension (used to detect the file type).", "type": "string" } }, "required": [ "content_base64", "filename" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "check_job", "description": "Get the status/result of an async job started by a long-running tool.", "inputSchema": { "additionalProperties": false, "properties": { "job_id": { "description": "The job id returned when the job was submitted.", "type": "string" } }, "required": [ "job_id" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "manage_collections", "description": "Create and manage collections: stored sets of items (e.g. faces) that a tool searches against. Tools that take a collection_id: image_face_recognition. Flow: create, then add_item once per file (returns the item ids it indexed), then call the tool with the collection_id; delete when done. Arguments per action: create(model, tool?, name?); list(tool?, model?, page?); get, delete, list_items(collection_id); add_item(collection_id, file); delete_item(collection_id, item_id).", "inputSchema": { "additionalProperties": false, "properties": { "action": { "enum": [ "create", "list", "get", "delete", "add_item", "list_items", "delete_item" ], "type": "string" }, "collection_id": { "description": "From create or list.", "type": "string" }, "file": { "description": "File to add (add_item). Pass a file ID (UUID) from upload_file, or a direct file URL.", "type": "string" }, "item_id": { "description": "Item to delete (delete_item), from add_item or list_items.", "type": "string" }, "model": { "description": "Provider the collection binds to (create; list filter). image_face_recognition: amazon.", "type": "string" }, "name": { "description": "Optional label (create).", "type": "string" }, "page": { "description": "Result page (list).", "minimum": 1, "type": "integer" }, "tool": { "description": "Tool the collection serves (create; list filter). Defaults to image_face_recognition.", "enum": [ "image_face_recognition" ], "type": "string" } }, "required": [ "action" ], "type": "object" } }, { "name": "audio_speech_to_text", "description": "Speech Recognition (or speech to text or voice to text) can recognize and transcribe spoken words (voice), that will be converted to text with or without diarization. It is also possible to filter profanity. The type of files allowed are: mp3, wav, m4a. If convert_to_wav option is set to true, then you can transcribe any type of audio or video files. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Audio file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: audio/*.", "type": "string" }, "language": { "description": "Language code in ISO format (e.g., 'en', 'fr', 'es')", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, assembly, deepgram, deepgram/base, deepgram/enhanced, deepgram/nova-3, gladia, google, gradium, gradium/stt-translate, greenpt, greenpt/green-s, greenpt/green-s-pro, microsoft, mistral, mistral/voxtral-mini-2602, mistral/voxtral-mini-latest, mistral/voxtral-mini-transcribe-3, mistral/voxtral-small-transcribe-3, openai. Call list_models for pricing.", "type": "string" }, "profanity_filter": { "default": false, "description": "Whether to filter profanity and replace inappropriate words with a series of asterisks", "type": "boolean" }, "speakers": { "default": 2, "description": "Number of speakers present in the audio", "minimum": 1, "type": "integer" }, "vocabulary": { "description": "List of words or composed words to be detected by the speech to text engine", "items": { "type": "string" }, "type": "array" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "audio_tts", "description": "Text-to-speech (TTS) is a technology that converts written text into spoken audio, enabling computers and digital devices to \"read\" text aloud. It is also known as speech synthesis, read aloud technology, or computer-generated speech.", "inputSchema": { "additionalProperties": false, "properties": { "audio_format": { "description": "Desired audio format (e.g., 'mp3', 'wav')", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon/neural, amazon/standard, deepgram/aura, deepgram/aura-2, elevenlabs, elevenlabs/eleven_flash_v2, elevenlabs/eleven_flash_v2_5, elevenlabs/eleven_multilingual_v2, elevenlabs/eleven_turbo_v2, elevenlabs/eleven_turbo_v2_5, elevenlabs/eleven_v3, google/casual, google/chirp-hd, google/chirp3-hd, google/gemini-2.5-flash-tts, google/gemini-2.5-pro-tts, google/gemini-3.1-flash-tts-preview, google/neural2, google/news, google/polyglot, google/standard, google/studio, google/wavenet, gradium, microsoft/neural, microsoft/neural-hd, mistral/voxtral-mini-tts-3, openai/gpt-4o-mini-tts, openai/tts-1, openai/tts-1-hd, ovhcloud/nvr-tts-de-de, ovhcloud/nvr-tts-en-us, ovhcloud/nvr-tts-es-es, ovhcloud/nvr-tts-it-it. Call list_models for pricing.", "type": "string" }, "speaking_pitch": { "description": "Increase or decrease the speaking pitch by a percentage from -100% to 100%, 0 is normal.", "maximum": 100, "minimum": -100, "type": "integer" }, "speaking_volume": { "description": "Increase or decrease the audio volume by a percentage from -100% to 100%, 0 is normal.", "maximum": 100, "minimum": -100, "type": "integer" }, "speed": { "description": "Speed multiplier for speech synthesis", "maximum": 4, "minimum": 0.25, "type": "number" }, "text": { "description": "Text to convert to speech", "minLength": 1, "type": "string" }, "voice": { "description": "Voice to synthesize with: an id or name from list_voices(model=...), matched case-insensitively. Omit it to use the model's default voice. An id the list doesn't know (e.g. your own cloned voice) is sent to the provider unchanged.", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "image_ai_detection", "description": "Determine whether an image was generated by AI or is a real photograph or artwork. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble, winstonai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_anonymization", "description": "Image Anonymization API, also known as image de-identification or image de-personalization, refers to the process of automatically removing personal or sensitive information from images. The main objective is to protect the privacy and security of individuals who may be depicted in images shared online or used for research purposes. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_background_removal", "description": "Background removal is a digital image processing technique designed to seamlessly eliminate the backdrop of a photo, leaving behind only the main subject. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai, clipdrop, photoroom, picsart, sentisight, stabilityai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_deepfake_detection", "description": "Detect whether a face in a real photo has been swapped or manipulated (face-swap deepfakes). For fully AI-generated images, use AI Image Detection instead. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble, sightengine. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_explicit_content", "description": "Explicit Content Detection detects adult only content in images, that is generally inappropriate for people under the age of 18 and includes nudity, sexual activity, pornography, violence, gore content, etc. (type of files allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, google, microsoft, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_face_compare", "description": "Compare two faces and decide whether they are from the same person. The API expects 2 images, reference and query, where the former is the ground truth (e.g. user's official ID) and the latter is the validation image (e.g. a selfie). File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file1": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "file2": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, base64, facepp. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file1", "file2" ], "type": "object" } }, { "name": "image_face_detection", "description": "Face Detection is a computer technology being used in a variety of applications that identifies human faces in digital images with different attributes like landmarks, sentiments and physical attire (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_face_recognition", "description": "Recognizing a face in an image is a more advanced feature than just detecting the face in the image. It allows the user to search for the detected face from a database of existing images and extract the faces that are most similar to the face displayed in the query image. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "collection_id": { "description": "Id of one of your collections. Make one with manage_collections (action='create', then add_item for each file to search against); action='list' shows the ones you have. 'model' must be the collection's provider.", "type": "string" }, "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "collection_id", "file" ], "type": "object" } }, { "name": "image_generation", "description": "Image Generation is an advanced feature that generates compelling images based on a given text prompt. It can easily produce high-quality and original images in a matter of seconds, without the need for specialized design skills or software File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "mask": { "description": "Optional inpainting mask. Must be paired with at least one reference image (otherwise the request returns 422). Support varies by model; models that do not accept a mask surface the error as status=\"fail\" with a provider message in the response body. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: bytedance, bytedance/seedream-4-0-250828, bytedance/seedream-4-5-251128, bytedance/seedream-5-0-260128, google, google/gemini-2.5-flash-image, google/gemini-3-pro-image-preview, infomaniak/flux, ionos/black-forest-labs/FLUX.1-schnell, ionos/black-forest-labs/FLUX.2-klein-4B, leonardo, leonardo/AlbedoBase XL, leonardo/Leonardo Anime XL, leonardo/Leonardo Diffusion XL, leonardo/Leonardo Kino XL, leonardo/Leonardo Lightning XL, leonardo/Leonardo Phoenix, leonardo/Leonardo Vision XL, leonardo/SDXL 0.9, minimax, minimax/image-01, openai, openai/gpt-image-1, openai/gpt-image-1-mini, openai/gpt-image-1.5, openai/gpt-image-2, ovhcloud/stable-diffusion-xl-base-v10, pruna/p-image, pruna/p-image-edit, pruna/p-image-ideogram, pruna/p-image-ideogram-low, pruna/p-image-ideogram-medium, pruna/p-image-ideogram-very-high, pruna/p-image-ideogram-very-low, replicate, replicate/anime-style, replicate/classic, replicate/vintedois-diffusion, stabilityai, stabilityai/stable-diffusion-xl-1024-v1-0. Call list_models for pricing.", "type": "string" }, "num_images": { "default": 1, "description": "Number of images to generate", "maximum": 10, "minimum": 1, "type": "integer" }, "reference_images": { "description": "Optional reference images. Plain file IDs/URLs are treated as ReferenceImage with kind=None. Support and per-model limits vary by model; models that do not accept reference images surface the error as status=\"fail\" with a provider message in the response body.", "items": {}, "maxItems": 64, "type": "array" }, "resolution": { "description": "Image resolution as a named size (e.g. '1024x1024'). Optional: providers may also accept native sizing knobs (width/height, aspect_ratio, image_size tier, etc.) in the top-level `provider_params` request field, next to `input` rather than inside it, in which case `provider_params` takes precedence.", "pattern": "^\\d+x\\d+$", "type": "string" }, "text": { "description": "Text prompt for image generation", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "image_logo_detection", "description": "Logo Detection is a powerful technology that enables the automatic identification and recognition of popular logos within an image. It provides accurate and efficient detection of known (and less known) brand logos. It's a valuable tool for a variety of industries, including advertising, retail, and e-commerce. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai, api4ai/v1, api4ai/v2, google, microsoft, openai, openai/gpt-4-turbo, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_object_detection", "description": "Object Detection is a computer vision technique that allows users to identify and locate (with bounding boxes) objects in an image. The detected objects can be animals, people, electronics, vehicles etc. (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, microsoft, sentisight. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr", "description": "Optical Character Recognition or Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text. The image can be a scanned document or a photo of a license plate, a road sign or anything else that contains text (type of files allowed: jpg, jpeg, png, tiff) . File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "language": { "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, ionos, ionos/lightonai/LightOnOCR-2-1B, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest, sentisight. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_async", "description": "OCR or Optical Character Recognition is also referred to as text recognition or text extraction. It allows users to extract text data from PDFs with multiple pages. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_financial_parser", "description": "Financial Parser API is a powerful and versatile tool designed to streamline your financial data extraction process. This cutting-edge API combines Optical Character Recognition (OCR) technology with advanced parsing capabilities to seamlessly extract and organize relevant information from invoices and receipts. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "document_type": { "default": "invoice", "description": "Specify the type of your document. Can be set to 'auto-detect' for automatic detection if the provider supports it.", "enum": [ "auto-detect", "invoice", "receipt" ], "type": "string" }, "file": { "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.", "type": "string" }, "language": { "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, eagledoc, extracta, google, klippa, microsoft, mindee, openai, openai/gpt-4o, tabscanner, veryfi. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_identity_parser", "description": "ID Document parsing technology allows users to automatically extract information from an ID Document such as passport, ID card, driving license and more. This API is ideal for developers looking to create applications that require identity verification or access control. It extracts information like name, date of birth, nationality, age and more. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, klippa, microsoft, mindee, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_resume_parser", "description": "Resume Parser enables users to extract various information from resumes (curriculum vitae, CV) that could be in a variety of formats and returns structured data (name, job list, education, skills) to automate their processing. (type of files allowed: pdf, jpg, jpeg, png) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, extracta, klippa, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_tables", "description": "OCR Table (Optical Character Recognition for tabular documents) allows users to analyze documents containing tables and returns a structured representation of the detected tables in the form of a Json object that can be converted to a CSV. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, google, microsoft. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "text_ai_detection", "description": "The AI Detection API is a tool designed to determine whether a given text was generated by an artificial intelligence chatbot, or a Language Model (LLM).", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: sapling, winstonai. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for AI detection, at least 300 characters long. Shorter texts carry too little signal to be scored reliably.", "minLength": 300, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_anonymization", "description": "The personally identifiable information (PII) detection feature can identify and redact sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Removing these personally identifiable information helps with the Anonymization of a text and privacy protection.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, limina, microsoft. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to detect personal information in", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_moderation", "description": "Text moderation scans text for offensive, sexually explicit or suggestive content, it also checks if there is any content of self-harm, violence, racist or hate speech.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: google, microsoft, openai, openai/text-moderation-007, openai/text-moderation-latest, openai/text-moderation-stable, ovhcloud/Qwen3Guard-Gen-0.6B, ovhcloud/Qwen3Guard-Gen-8B. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to moderate", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_named_entity_recognition", "description": "Named Entity Recognition (also called entity identification or extraction) is an information extraction technique that automatically identifies named entities in a text and classifies them into predefined categories such as dates, persons names, company names, dates, products etc.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, microsoft, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for named entities", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_plagia_detection", "description": "The Plagiarism Detection API is a tool designed to scan a content string for plagiarism using a plagiarism detection module", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: winstonai. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text content on which plagiarism detection will be run", "minLength": 1, "type": "string" }, "title": { "description": "Content title", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_spell_check", "description": "Spell Check analyzes the inputted text by comparing it to a dictionary of correctly spelled words to identify and highlight any spelling errors or grammatical mistakes.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: prowritingaid, sapling. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to be spell-checked", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_topic_extraction", "description": "Topic analysis is a Natural Language Processing (NLP) technique that allows us to automatically extract meaning from text by identifying recurrent themes or topics.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: google, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for topics", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "translation_automatic_translation", "description": "Automatic translation or machine translation (MT) is the process of automatically translating a text from one language to another language. The aim of it is to enable people to communicate and access information in different languages, without the need for a human translator.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: amazon, deepl, google, microsoft, modernmt, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "source_language": { "description": "Source language code", "minLength": 1, "type": "string" }, "target_language": { "description": "Target language code", "minLength": 1, "type": "string" }, "text": { "description": "Text to translate", "minLength": 1, "type": "string" } }, "required": [ "model", "text", "target_language" ], "type": "object" } }, { "name": "translation_document_translation", "description": "Document Translation API translates whole documents in supported languages and various file formats (like pdf or doc) while keeping their structure intact. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Document file ID from /v3/upload or direct file URL (PDF, DOCX, PPTX) Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/vnd.openxmlformats-officedocument.presentationml.presentation.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: deepl, google. Call list_models for pricing.", "type": "string" }, "source_language": { "description": "Source language code", "minLength": 1, "type": "string" }, "target_language": { "description": "Target language code", "minLength": 1, "type": "string" } }, "required": [ "model", "file", "target_language" ], "type": "object" } }, { "name": "video_deepfake_detection", "description": "Detect deepfake and synthetically manipulated video. Returns an overall deepfake score and prediction, along with per-frame scores when the provider supplies them. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Video file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "video_generation", "description": "The Video Generation API enables easy creation of high-quality videos from text,and images, perfect for marketing, education, and more—all through one integration. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "dimension": { "default": "1280x720", "description": "Video resolution in 'widthxheight' format (e.g., '1280x720')", "pattern": "^\\d+x\\d+$", "type": "string" }, "duration": { "description": "Length of the generated video in seconds. Omit to use the model's default duration.", "maximum": 120, "minimum": 1, "type": "integer" }, "file": { "description": "Initial keyframe image (JPEG or PNG) file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/jpeg, image/png.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: bytedance, bytedance/dreamina-seedance-2-0-260128, bytedance/dreamina-seedance-2-0-fast-260128, bytedance/dreamina-seedance-2-0-mini-260615, bytedance/dreamina-seedance-2-5-260628, bytedance/seedance-1-0-pro-250528, bytedance/seedance-1-0-pro-fast-251015, bytedance/seedance-1-5-pro-251215, minimax, minimax/MiniMax-Hailuo-02, minimax/MiniMax-Hailuo-2.3, minimax/S2V-01, minimax/T2V/I2V-01-Director, openai, openai/sora-2, openai/sora-2-pro, pixverse, pixverse/c1, pixverse/v5, pixverse/v5.5, pixverse/v6, pruna, pruna/p-video, pruna/p-video-2, pruna/p-video-2-pro, pruna/p-video-2-pro-cost, pruna/p-video-2-pro-quality, pruna/p-video-animate, pruna/p-video-avatar, pruna/p-video-edit, xai/grok-imagine-video-1.5, xai/grok-imagine-video-1.5-lite. Call list_models for pricing.", "type": "string" }, "seed": { "description": "Random seed for generation reproducibility (0 to 2,147,483,646). Omit for varied output.", "maximum": 2147483646, "minimum": 0, "type": "integer" }, "text": { "description": "Text prompt describing the content and style of the video to generate", "minLength": 1, "type": "string" }, "video": { "description": "Source video to edit, for models that edit a video (their `requires_video` is true in /v3/info). The output keeps the source's length, which is what is billed, so `duration` and `dimension` do not apply to them. Other models refuse it. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "web_batch_scrape", "description": "Scrape many URLs in one request and return each page's content. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.", "type": "string" }, "urls": { "description": "Explicit list of URLs to scrape (async job)", "items": { "type": "string" }, "minItems": 1, "type": "array" } }, "required": [ "model", "urls" ], "type": "object" } }, { "name": "web_crawl", "description": "Crawl a site from a starting URL and return the content of its pages. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "Root URL to crawl (async job)", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_map", "description": "Discover and return the list of URLs on a site (a sitemap-style link map).", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "Root URL to map (discover its links)", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_research", "description": "Run deep, multi-step web research on a query and return a synthesized answer with sources. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, linkup, tavily. Call list_models for pricing.", "type": "string" }, "prompt": { "description": "Natural-language research task for the agent", "minLength": 1, "type": "string" }, "reasoning_depth": { "default": "L", "description": "Research reasoning-effort tier (billed per tier; priced pre-call)", "enum": [ "S", "M", "L", "XL" ], "type": "string" }, "schema": { "description": "JSON schema describing the structured output", "type": "object" } }, "required": [ "model", "prompt" ], "type": "object" } }, { "name": "web_scraping", "description": "Fetch a single URL and return its clean content as markdown, text, or HTML, with optional JavaScript rendering.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "URL of the web page to scrape", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_search", "description": "Search the web for a query and return ranked results (title, URL, and a snippet or the page content).", "inputSchema": { "additionalProperties": false, "properties": { "depth": { "default": "standard", "description": "Search depth tier. `deep` is refused with a 400 on deepseek, perplexityai and zai, which run one tier only.", "enum": [ "standard", "deep" ], "type": "string" }, "max_results": { "description": "Max number of search results to return", "minimum": 1, "type": "integer" }, "model": { "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, perplexityai, tavily, zai. Call list_models for pricing.", "type": "string" }, "query": { "description": "The web search query", "minLength": 1, "type": "string" } }, "required": [ "model", "query" ], "type": "object" } }, { "name": "web_structured_extraction", "description": "Extract structured data from one or more web pages against a schema or prompt. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.", "type": "string" }, "prompt": { "description": "Natural-language description of what to extract", "type": "string" }, "schema": { "description": "JSON schema describing the structured output", "type": "object" }, "urls": { "description": "URLs to extract structured data from (async job)", "items": { "type": "string" }, "minItems": 1, "type": "array" } }, "required": [ "model", "urls" ], "type": "object" } } ], "schemaTokens": 10725, "changedAt": "2026-11-07T01:44:01.27972989Z", "check": { "checker": "anchor-check/1.0", "totalTokens": 10725, "counts": { "error": 0, "note": 1, "warn": 49 }, "findings": [ { "rule": "TC11", "severity": "warn", "tool": "manage_collections", "message": "1 parameter without a description: action", "fix": "Describe each one: format, units, an example, and what happens when it's left out." }, { "rule": "TC12", "severity": "warn", "tool": "image_generation", "message": "no type for reference_images[]", "fix": "Give every parameter a type (or an enum)." }, { "rule": "TC13", "severity": "warn", "tool": "web_research", "message": "schema (object with no properties)", "fix": "Declare the properties (or additionalProperties with a schema) and the array's items." }, { "rule": "TC13", "severity": "warn", "tool": "web_structured_extraction", "message": "schema (object with no properties)", "fix": "Declare the properties (or additionalProperties with a schema) and the array's items." }, { "rule": "TC14", "severity": "warn", "tool": "image_face_recognition", "message": "allowed values are in the description, not an enum: collection_id", "fix": "Move them into enum." }, { "rule": "TC14", "severity": "warn", "tool": "image_generation", "message": "allowed values are in the description, not an enum: resolution", "fix": "Move them into enum." }, { "rule": "TC16", "severity": "warn", "tool": "audio_speech_to_text", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "audio_tts", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "check_job", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "image_ai_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_anonymization", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_background_removal", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_deepfake_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_explicit_content", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_compare", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_recognition", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_generation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_logo_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_object_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "list_models", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "list_voices", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "manage_collections", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_async", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_financial_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_identity_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_resume_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_tables", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_ai_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_anonymization", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_moderation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_named_entity_recognition", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_plagia_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_spell_check", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "text_topic_extraction", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "translation_automatic_translation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "translation_document_translation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "upload_file", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "video_deepfake_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "video_generation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_batch_scrape", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_crawl", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_map", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_research", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_scraping", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_search", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "web_structured_extraction", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC23", "severity": "warn", "message": "42 tools", "fix": "Offer a smaller default toolset and let clients opt into the rest." }, { "rule": "TC24", "severity": "note", "message": "38 of 42 tools have no outputSchema", "fix": "Declare outputSchema for tools that return structured data, and return structuredContent that matches it." } ] } }, "updatedAt": "2026-11-07T19:22:04.810042763Z" } }, "answer": "Eden AI scores 59.9 (C) on agent readiness against Simplismart's 29.5 (F), and leads in every scored category.", "b": { "slug": "simplismart", "name": "Simplismart", "vendor": "Verute Technologies Private Limited", "vendorUrl": "https://simplismart.ai", "kind": "http-api", "category": "inference", "summary": "Simplismart is an inference platform for open models. It runs 150+ models on shared pay-per-token endpoints with an OpenAI-compatible API, and handles dedicated GPU deployments, bring-your-own-cloud clusters and fine-tuning jobs.", "url": "https://www.anchorterminal.com/tools/simplismart", "markdownUrl": "https://www.anchorterminal.com/tools/simplismart.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/simplismart.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/simplismart.json", "dns": "simplismart.grade.anchorterminal.com", "license": "Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.simplismart.live", "packages": [ { "registry": "pypi", "name": "simplismart-sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys made under Settings, API Keys. Each key has a unique name and an expiry chosen at creation; non-expiring keys need a request to support. Keys return 401 after midnight UTC on the expiry date and can be deleted at once. The Python SDK and CLI use a separate Playground token. Organisation roles are Admin, Member and Billing User, and workspaces scope models and deployments.", "pricing": "usage", "pricingNotes": "Shared endpoints are priced per 1M tokens, per image or per audio minute, such as Llama 3.1 8B at $0.13 and DeepSeek-V3 at $0.90 per 1M tokens. Dedicated GPUs run from $1.20 (T4) to $5.20 (H200) per GPU-hour. Prepaid credits at $1 each; new organisations may receive $5 of free credits.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs (llms.txt index, billing, API keys and API reference pages) or on the pricing page, checked 28 October 2026. Credits are bought by card, UPI or netbanking, or billed postpaid.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-28" }, "docsUrl": "https://docs.simplismart.ai", "llmsTxt": "https://docs.simplismart.ai/llms.txt", "openapi": "https://docs.simplismart.ai/openapi-specs/playground/llama-8b.yaml", "capabilities": [ "inference.llm", "inference.open-weights", "speech.stt", "image.generate", "compute.endpoints", "finetune.sft", "finetune.lora", "finetune.preference", "finetune.rl" ], "tags": [ "hosted", "model", "open-weights", "usage-based", "openai-compatible", "openapi", "llms-txt", "python", "dedicated-endpoints", "byoc", "fine-tuning" ], "lastRelease": "2026-10-19", "graded": true, "anchor": { "graded": true, "score": 29.5, "grade": "F", "agentReady": false, "rank": 1424, "ranked": true, "rankOf": 1510, "categoryRank": 42, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 17, "maintenance": 42, "payments": 25, "reliability": 15, "schema": 51, "security": 35, "transparency": 29 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-28" }, "negative": 0, "verdict": "Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data.", "bestFor": "Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.", "strengths": [ "Public per-unit prices without a login, such as Llama 3.1 8B at $0.13 per 1M tokens and Whisper v3 Turbo at $0.0018 per audio minute", "API keys are named, carry an expiry date chosen at creation, return 401 after expiry and can be deleted at once", "Markdown docs and an llms.txt index, with OpenAPI 3.1 files for seven LLMs, Whisper and Flux", "Shared endpoints, dedicated GPU deployments and bring-your-own-cloud clusters sit on one account, with workspaces and organisation roles" ], "weaknesses": [ "No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages", "No status page, incident history or SLA document found; the 99.99% uptime figure is a homepage claim", "Tool calling, structured output, prompt caching and context lengths are not documented for the shared endpoints", "The terms (13 January 2023) and privacy policy cover the website and say nothing about prompt retention or training on API data", "The pricing page lists older models (Llama 3.1, DeepSeek-R1) and omits Gemma 4 31B, the model the quickstart uses" ], "agentNotes": [ "Point an OpenAI-compatible client at https://api.simplismart.live with SIMPLISMART_API_KEY as a Bearer token, and take model ids from the marketplace or the per-model API pages.", "Set a key expiry and rotate before midnight UTC on the expiry date, because an expired key returns 401.", "Cap retries yourself with exponential backoff, because no rate limits, 429 format or retry guidance are published.", "Check that a model supports tools or JSON output with a test call before relying on it, because neither is documented.", "Confirm the per-token price of the exact model in the console before running large jobs, because the public price list is incomplete." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "F", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 29.5 } ], "editorialScores": { "ergonomics": 17, "maintenance": 42, "payments": 25, "reliability": 15, "schema": 51, "security": 35, "transparency": 14 }, "provenanceScore": 44, "checked": { "categories": { "ergonomics": "2026-10-28", "maintenance": "2026-10-28", "payments": "2026-10-28", "reliability": "2026-10-28", "schema": "2026-10-28", "security": "2026-10-28", "transparency": "2026-10-28" }, "last": "2026-10-28", "lastMoved": "2026-10-30", "oldest": "2026-10-28", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.simplismart.live/chat/completions' -H 'Content-Type: application/json' -H \"Authorization: Bearer $SIMPLISMART_API_KEY\" -d '{\"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/simplismart" }, "area": "models", "unitPrices": [ { "item": "Llama 3.1 8B (shared)", "unit": "1m-tokens", "usd": 0.13, "note": "Single per-1M-token rate on the pricing page, checked 28 October 2026; input and output are not priced separately" }, { "item": "Llama 3.3 70B (shared)", "unit": "1m-tokens", "usd": 0.74, "note": "Pricing page, checked 28 October 2026" }, { "item": "DeepSeek-V3 (shared)", "unit": "1m-tokens", "usd": 0.9, "note": "Pricing page, checked 28 October 2026" }, { "item": "Whisper v3 Turbo (shared)", "unit": "audio-minute", "usd": 0.0018, "note": "Pricing page, checked 28 October 2026" }, { "item": "Flux Dev (shared, 1024x1024)", "unit": "image", "usd": 0.03, "note": "Pricing page, checked 28 October 2026" }, { "item": "NVIDIA H100, dedicated", "unit": "gpu-hour", "usd": 5, "note": "Pricing page table order, checked 28 October 2026; a Simplismart article gives $4.00 per hour" } ], "provenance": { "legalEntity": "Verute Technologies Private Limited", "domain": "simplismart.ai", "domainRegistered": "", "endpointOnVendorDomain": false, "terms": "https://simplismart.ai/terms-of-service", "privacy": "https://simplismart.ai/privacy-policy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-28", "notes": [ "The terms (last updated 13 January 2023) and privacy policy (effective 13 January 2023) name Verute Technologies Private Limited, Indian law and an address on Residency Road, Bengaluru. Both define the Service as the simplismart.ai website.", "The inference API answers on api.simplismart.live, a separate domain named in the docs. Domain registration was not checked.", "No status page found. The docs and site link none, and status.simplismart.ai could not be reached from our network.", "No changelog found in the docs sitemap or llms.txt. Model additions appear as blog posts.", "simplismart.ai/.well-known/security.txt answered 404." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/simplismart.json", "live": { "slug": "simplismart", "probe": { "target": "https://api.simplismart.live", "method": "get", "lastAt": "2026-11-07T19:22:33.217760995Z", "lastOk": true, "lastStatus": 405, "lastMs": 63, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 60, "p95ms24h": 169, "samples24h": 238, "samples30d": 2573, "days": [ { "date": "2026-10-28", "probes": 208, "ok": 208 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "versions": [ { "registry": "pypi", "name": "simplismart-sdk", "version": "0.1.15", "released": "2026-11-02", "seenAt": "2026-11-07T00:06:08.735466052Z" } ], "pypiWeekly": 186, "securityTxt": { "url": "https://simplismart.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:22.590979779Z" }, "llmsTxt": { "url": "https://docs.simplismart.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:56.047475338Z" }, "domain": { "domain": "simplismart.ai", "registered": "2022-11-18", "source": "https://rdap.identitydigital.services/rdap/domain/simplismart.ai", "checkedAt": "2026-11-01T14:28:09.738527702Z" }, "pages": [ { "url": "https://simplismart.ai/privacy-policy", "kind": "privacy", "status": 304, "checkedAt": "2026-11-07T14:19:55.485469388Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "bd2d6d5ffe37" }, { "url": "https://simplismart.ai/terms-of-service", "kind": "terms", "status": 304, "checkedAt": "2026-11-07T14:19:59.722810598Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "94fe8807daf7" } ], "updatedAt": "2026-11-07T19:22:33.217760995Z" } }, "edges": [ { "by": 58, "category": "ergonomics", "leads": "eden-ai", "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). The LiveKit guide calls the LLM API fully OpenAI-compatible, but no page documents tools or tool_choice, and the OpenAPI files allow only system, user and assistant roles (3 of 20). No structured-output or JSON mode documented (0 of 15). No prompt caching documented for shared endpoints (0 of 15). Context lengths are not stated per model; output is capped at 4,096 tokens in the API files (3 of 15). No batch API for shared endpoints (0 of 10). Inference goes through the OpenAI client; the simplismart-sdk Python package and CLI manage repositories and deployments, not inference, and a community Pipecat package exists (5 of 10). Expired keys return a documented 401, and the SDK exposes status_code, message and payload, but no error codes or bodies are listed for the inference API (6 of 15). 3+0+0+3+0+5+6 = 17." }, "scores": { "a": 75, "b": 17 } }, { "by": 47, "category": "security", "leads": "eden-ai", "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. Named Bearer keys with an expiry chosen at creation, a 401 after expiry and immediate deletion. No scopes or per-key limits found, keys belong to the organisation, and the SDK uses a separate Playground token (20 of 30). No statement on training on API data in the terms, the privacy policy, the AI policy or the docs (0 of 20). No retention or zero-retention statement for prompts and outputs. The privacy policy covers the website only (0 of 15). The Usage page shows request counts and a per-request timeline per model, and an LLM metrics call returns token counts and timings per request id. A Simplismart article claims exportable audit trails, not documented (8 of 15). The homepage shows GDPR, ISO 27001 v2022 and AICPA SOC 2 badges, and a Simplismart article says it holds a SOC 2 Type 2 report, available on request. No trust centre was reachable, security.txt answered 404, and no disclosure policy or bug bounty was found (7 of 20). 20+0+0+8+7 = 35." }, "scores": { "a": 82, "b": 35 } }, { "by": 30, "category": "schema", "leads": "eden-ai", "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": "Model reading. OpenAPI 3.1 files for seven LLMs and 3.0 or 3.1 files for Whisper, Flux, an LLM metrics call and training jobs. They cover a handful of the 150+ models, omit tools and response_format, show a streaming `delta` as the non-streaming response, and several name hosts on s9t.link instead of api.simplismart.live. The Llama 4 Maverick file gives `llama3_1` as its only model id, and /api-reference/openapi.json is the Flux spec (12 of 25). llms.txt and a Markdown copy of each docs page (10). The docs say when to use shared or dedicated endpoints; model pages carry one-line descriptions (10 of 20). Roles are enums, temperature is bounded 0 to 2, max_tokens 1 to 4096, and messages and model are required (10 of 15). curl and OpenAI-client Python examples. Errors are bare 400, 401 and 500 descriptions, plus an SDK example of a 404 payload (7 of 15). No changelog. Every spec reads version 1.0.0 (2 of 15). 12+10+10+10+7+2 = 51." }, "scores": { "a": 81, "b": 51 } }, { "by": 26, "category": "transparency", "leads": "eden-ai", "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. The terms, last updated 13 January 2023, name Verute Technologies Private Limited and Indian law but define the Service as the website, grant Simplismart a licence to use and redistribute posted Content, bar robots and automatic access, and rule out refunds. No API or platform terms were found (8 of 30). The privacy policy, effective 13 January 2023, is a website policy that says personal data is processed in India. It says nothing about prompts, outputs, logs or training, and no DPA, retention period or subprocessor list was found. A Simplismart article claims GDPR and HIPAA support (3 of 30). No deprecation policy or dated removals (0 of 20). Data goes to India per the privacy policy, and an article says workloads are kept in approved regions by scheduling policy. No subprocessor or hosting-provider list (3 of 20). 8+3+0+3 = 14." }, "scores": { "a": 55, "b": 29 } }, { "by": 18, "category": "reliability", "leads": "eden-ai", "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": "Hosted reading. No status page found. The docs and site link none, a search found none, and status.simplismart.ai could not be reached from our network (0). No readable incident history (5). No request or token rate limits are published for shared endpoints. The docs give GPU quotas for training, compilation and private deployments only, 1 H100 and 1 L40 on the Quotas page and 8 of each on the Organisation page (0). No 429 response, Retry-After header or retry guidance found; the OpenAPI files list only 400, 401 and 500 (0). No SLA document found. The homepage claims 99.99% uptime and a Simplismart post calls its autoscaling SLA-backed, but no terms state a commitment, and the terms provide the service as is (0). Shared endpoints carry no beta label, while Muse Spark Open is in beta (10). 0+5+0+0+0+10 = 15." }, "scores": { "a": 33, "b": 15 } }, { "by": 16, "category": "maintenance", "leads": "eden-ai", "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 for a closed service. Muse Spark Open was added in beta on 19 October 2026, and the docs sitemap shows pages changed on 7 October (30). No deprecation policy or notice period found (0 of 12). One dated model addition in the 90 days to 28 October and no recorded removals; the pricing page still lists Llama 3.1 405B and DeepSeek-R1, which the API reference doesn't cover, so the live model set is unclear (2 of 8). No public changelog or community channel. Support is support@simplismart.ai and a contact form, not tested (4 of 15). SDK issue replies not read, because github.com gave no readable robots.txt (0 of 10). simplismart-sdk for Python, documented with a CLI, and the OpenAI client for inference. No TypeScript SDK, and the PyPI page answered with a browser challenge, so the version and date are unchecked (6 of 15). CI not checked (0 of 10). 30+0+2+4+0+6+0 = 42." }, "scores": { "a": 58, "b": 42 } } ], "facts": [ { "a": "Model router", "b": "HTTP API", "name": "Kind" }, { "a": "Eden AI SAS", "b": "Verute Technologies Private Limited", "name": "Vendor" }, { "a": "https://mcp.edenai.run/mcp", "b": "https://api.simplismart.live", "name": "Hosted endpoint" }, { "a": "HTTP, Streamable HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "none", "b": "Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-05", "b": "2026-10-19", "name": "Last release" }, { "a": "2026-10-22", "b": "2023-01-13", "name": "Terms last updated" }, { "a": "2026-10-22", "b": "2023-01-13", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "yes", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" } ], "faq": [ { "answer": "Eden AI scores 59.9 (C) on agent readiness against Simplismart's 29.5 (F), and leads in every scored category.", "question": "Which is better for AI agents, Eden AI or Simplismart?" }, { "answer": "Both need an API key.", "question": "Do Eden AI and Simplismart need an API key?" }, { "answer": "Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and Simplismart at https://api.simplismart.live.", "question": "Can an agent call Eden AI and Simplismart without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 33 against 15", "Schema \u0026 documentation, 81 against 51", "Agent ergonomics, 75 against 17", "Security \u0026 auth, 82 against 35", "Payments \u0026 pricing, 30 against 25", "Maintenance \u0026 community, 58 against 42", "Transparency \u0026 trust, 55 against 29" ], "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": null, "also": null, "goodFor": "Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.", "slug": "simplismart", "watchFor": "No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages" } ], "history": { "eden-ai": null, "simplismart": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 29.7, "fromGrade": "F", "to": 29.5, "toGrade": "F" } ] }, "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-simplismart.json", "title": "Amazon Bedrock vs Simplismart", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart" }, { "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-simplismart.json", "title": "Claude API vs Simplismart", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-simplismart.json", "title": "Antseed vs Simplismart", "url": "https://www.anchorterminal.com/compare/antseed-vs-simplismart" }, { "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-simplismart.json", "title": "Azure OpenAI in Foundry Models vs Simplismart", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-simplismart" }, { "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-simplismart.json", "title": "BlockRun.AI vs Simplismart", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-simplismart" }, { "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-simplismart.json", "title": "Cerebras Inference vs Simplismart", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart" }, { "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-simplismart.json", "title": "Cloudflare AI Gateway vs Simplismart", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-simplismart" }, { "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-simplismart.json", "title": "Cloudflare Workers AI vs Simplismart", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-simplismart" }, { "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-simplismart.json", "title": "Cohere Chat API (Command models) vs Simplismart", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-simplismart" }, { "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-simplismart.json", "title": "DeepInfra vs Simplismart", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-simplismart" }, { "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-simplismart.json", "title": "DeepSeek API vs Simplismart", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-simplismart" }, { "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": 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{ "json": "https://www.anchorterminal.com/compare/openrouter-vs-simplismart.json", "title": "OpenRouter vs Simplismart", "url": "https://www.anchorterminal.com/compare/openrouter-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-simplismart.json", "title": "Prism Inference vs Simplismart", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-simplismart.json", "title": "Router.com (Ramp Router) vs Simplismart", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.json", "title": "Beam 1.0 vs Simplismart", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-simplismart.json", "title": "RouterPlus vs Simplismart", "url": "https://www.anchorterminal.com/compare/routerplus-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-simplismart.json", "title": "SambaCloud vs Simplismart", "url": "https://www.anchorterminal.com/compare/sambanova-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart.json", "title": "SiliconFlow vs Simplismart", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api.json", "title": "Simplismart vs StepFun API", "url": "https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-swe-2-flash.json", "title": "Simplismart vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/simplismart-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub.json", "title": "Simplismart vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference.json", "title": "Simplismart vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway.json", "title": "Simplismart vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.json", "title": "Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api.json", "title": "Simplismart vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/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" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-simplismart.json", "title": "Nemotron 3.5 Super VL vs Simplismart", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-simplismart" } ], "panel": null, "scores": [ { "by": 18, "eden-ai": 33, "edge": "eden-ai", "key": "reliability", "name": "Reliability", "simplismart": 15, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 30, "eden-ai": 81, "edge": "eden-ai", "key": "schema", "name": "Schema \u0026 documentation", "simplismart": 51, "weight": 13 }, { "by": 58, "eden-ai": 75, "edge": "eden-ai", "key": "ergonomics", "name": "Agent ergonomics", "simplismart": 17, "weight": 13 }, { "by": 47, "eden-ai": 82, "edge": "eden-ai", "key": "security", "name": "Security \u0026 auth", "simplismart": 35, "weight": 14 }, { "by": 5, "eden-ai": 30, "edge": "eden-ai", "key": "payments", "name": "Payments \u0026 pricing", "simplismart": 25, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 16, "eden-ai": 58, "edge": "eden-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "simplismart": 42, "weight": 7 }, { "by": 26, "eden-ai": 55, "edge": "eden-ai", "key": "transparency", "name": "Transparency \u0026 trust", "simplismart": 29, "weight": 7 } ], "summary": "Eden AI scores 59.9 (C) on agent readiness against Simplismart's 29.5 (F), and leads in every scored category. 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.", "simplismart": "Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart", "json": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.min.md" }, "markdown": "Eden AI scores 59.9 (C) on agent readiness against Simplismart's 29.5 (F), and leads in every scored category. Both do llm inference.\n\n- Eden AI: grade C, 59.9/100, rank #675 of 1510. Markdown https://www.anchorterminal.com/tools/eden-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n- Simplismart: grade F, 29.5/100, rank #1424 of 1510. Markdown https://www.anchorterminal.com/tools/simplismart.md · JSON https://www.anchorterminal.com/api/v1/tools/simplismart.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Eden AI (C)\n\nGood for: Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.\n\nAhead on:\n- Reliability, 33 against 15\n- Schema \u0026 documentation, 81 against 51\n- Agent ergonomics, 75 against 17\n- Security \u0026 auth, 82 against 35\n- Payments \u0026 pricing, 30 against 25\n- Maintenance \u0026 community, 58 against 42\n- Transparency \u0026 trust, 55 against 29\n\nWatch for: No public status page, incident history or SLA found\n\n### Simplismart (F)\n\nGood for: Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.\n\nWatch for: No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages\n\n\n## Why the edge\n\n### Agent ergonomics: Eden AI +58\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- Simplismart (17): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). The LiveKit guide calls the LLM API fully OpenAI-compatible, but no page documents tools or tool_choice, and the OpenAPI files allow only system, user and assistant roles (3 of 20). No structured-output or JSON mode documented (0 of 15). No prompt caching documented for shared endpoints (0 of 15). Context lengths are not stated per model; output is capped at 4,096 tokens in the API files (3 of 15). No batch API for shared endpoints (0 of 10). Inference goes through the OpenAI client; the simplismart-sdk Python package and CLI manage repositories and deployments, not inference, and a community Pipecat package exists (5 of 10). Expired keys return a documented 401, and the SDK exposes status_code, message and payload, but no error codes or bodies are listed for the inference API (6 of 15). 3+0+0+3+0+5+6 = 17.\n\n### Security \u0026 auth: Eden AI +47\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- Simplismart (35): Model reading. Named Bearer keys with an expiry chosen at creation, a 401 after expiry and immediate deletion. No scopes or per-key limits found, keys belong to the organisation, and the SDK uses a separate Playground token (20 of 30). No statement on training on API data in the terms, the privacy policy, the AI policy or the docs (0 of 20). No retention or zero-retention statement for prompts and outputs. The privacy policy covers the website only (0 of 15). The Usage page shows request counts and a per-request timeline per model, and an LLM metrics call returns token counts and timings per request id. A Simplismart article claims exportable audit trails, not documented (8 of 15). The homepage shows GDPR, ISO 27001 v2022 and AICPA SOC 2 badges, and a Simplismart article says it holds a SOC 2 Type 2 report, available on request. No trust centre was reachable, security.txt answered 404, and no disclosure policy or bug bounty was found (7 of 20). 20+0+0+8+7 = 35.\n\n### Schema \u0026 documentation: Eden AI +30\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- Simplismart (51): Model reading. OpenAPI 3.1 files for seven LLMs and 3.0 or 3.1 files for Whisper, Flux, an LLM metrics call and training jobs. They cover a handful of the 150+ models, omit tools and response_format, show a streaming `delta` as the non-streaming response, and several name hosts on s9t.link instead of api.simplismart.live. The Llama 4 Maverick file gives `llama3_1` as its only model id, and /api-reference/openapi.json is the Flux spec (12 of 25). llms.txt and a Markdown copy of each docs page (10). The docs say when to use shared or dedicated endpoints; model pages carry one-line descriptions (10 of 20). Roles are enums, temperature is bounded 0 to 2, max_tokens 1 to 4096, and messages and model are required (10 of 15). curl and OpenAI-client Python examples. Errors are bare 400, 401 and 500 descriptions, plus an SDK example of a 404 payload (7 of 15). No changelog. Every spec reads version 1.0.0 (2 of 15). 12+10+10+10+7+2 = 51.\n\n### Transparency \u0026 trust: Eden AI +26\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- Simplismart (29): Closed service. The terms, last updated 13 January 2023, name Verute Technologies Private Limited and Indian law but define the Service as the website, grant Simplismart a licence to use and redistribute posted Content, bar robots and automatic access, and rule out refunds. No API or platform terms were found (8 of 30). The privacy policy, effective 13 January 2023, is a website policy that says personal data is processed in India. It says nothing about prompts, outputs, logs or training, and no DPA, retention period or subprocessor list was found. A Simplismart article claims GDPR and HIPAA support (3 of 30). No deprecation policy or dated removals (0 of 20). Data goes to India per the privacy policy, and an article says workloads are kept in approved regions by scheduling policy. No subprocessor or hosting-provider list (3 of 20). 8+3+0+3 = 14.\n\n### Reliability: Eden AI +18\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- Simplismart (15): Hosted reading. No status page found. The docs and site link none, a search found none, and status.simplismart.ai could not be reached from our network (0). No readable incident history (5). No request or token rate limits are published for shared endpoints. The docs give GPU quotas for training, compilation and private deployments only, 1 H100 and 1 L40 on the Quotas page and 8 of each on the Organisation page (0). No 429 response, Retry-After header or retry guidance found; the OpenAPI files list only 400, 401 and 500 (0). No SLA document found. The homepage claims 99.99% uptime and a Simplismart post calls its autoscaling SLA-backed, but no terms state a commitment, and the terms provide the service as is (0). Shared endpoints carry no beta label, while Muse Spark Open is in beta (10). 0+5+0+0+0+10 = 15.\n\n### Maintenance \u0026 community: Eden AI +16\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- Simplismart (42): Model reading for a closed service. Muse Spark Open was added in beta on 19 October 2026, and the docs sitemap shows pages changed on 7 October (30). No deprecation policy or notice period found (0 of 12). One dated model addition in the 90 days to 28 October and no recorded removals; the pricing page still lists Llama 3.1 405B and DeepSeek-R1, which the API reference doesn't cover, so the live model set is unclear (2 of 8). No public changelog or community channel. Support is support@simplismart.ai and a contact form, not tested (4 of 15). SDK issue replies not read, because github.com gave no readable robots.txt (0 of 10). simplismart-sdk for Python, documented with a CLI, and the OpenAI client for inference. No TypeScript SDK, and the PyPI page answered with a browser challenge, so the version and date are unchecked (6 of 15). CI not checked (0 of 10). 30+0+2+4+0+6+0 = 42.\n\n## Score by category\n\n| Category | Weight | Eden AI | Simplismart | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 33 | 15 | Eden AI +18 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 81 | 51 | Eden AI +30 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 17 | Eden AI +58 |\n| Security \u0026 auth | 14% (17.5 this run) | 82 | 35 | Eden AI +47 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 25 | Eden AI +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 58 | 42 | Eden AI +16 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 29 | Eden AI +26 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.9 · C** | **29.5 · F** | |\n\n## Facts side by side\n\n| Fact | Eden AI | Simplismart |\n| --- | --- | --- |\n| Kind | Model router | HTTP API |\n| Vendor | Eden AI SAS | Verute Technologies Private Limited |\n| Hosted endpoint | `https://mcp.edenai.run/mcp` | `https://api.simplismart.live` |\n| Transports | HTTP, Streamable HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-05 | 2026-10-19 |\n| Terms last updated | 2026-10-22 | 2023-01-13 |\n| Privacy policy last updated | 2026-10-22 | 2023-01-13 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n\n## How the scores have moved\n\n### Eden AI\n\nNo score change since it was listed.\n\n### Simplismart\n\n- -0.2 on 30 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**Simplismart.** Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data.\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### Simplismart\n\n1. Point an OpenAI-compatible client at https://api.simplismart.live with SIMPLISMART_API_KEY as a Bearer token, and take model ids from the marketplace or the per-model API pages.\n2. Set a key expiry and rotate before midnight UTC on the expiry date, because an expired key returns 401.\n3. Cap retries yourself with exponential backoff, because no rate limits, 429 format or retry guidance are published.\n4. Check that a model supports tools or JSON output with a test call before relying on it, because neither is documented.\n5. Confirm the per-token price of the exact model in the console before running large jobs, because the public price list is incomplete.\n\n## Questions\n\n### Which is better for AI agents, Eden AI or Simplismart?\n\nEden AI scores 59.9 (C) on agent readiness against Simplismart's 29.5 (F), and leads in every scored category.\n\n### Do Eden AI and Simplismart need an API key?\n\nBoth need an API key.\n\n### Can an agent call Eden AI and Simplismart without installing anything?\n\nYes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and Simplismart at https://api.simplismart.live.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.json, and with the fewest tokens: https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"eden-ai\", \"b\": \"simplismart\"}`. From a terminal: `anchor compare eden-ai simplismart`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/eden-ai.json and https://www.anchorterminal.com/api/v1/tools/simplismart.json\n\n## Other comparisons with Eden AI or Simplismart\n\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Amazon Bedrock vs Simplismart](https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.md)\n- [Claude API vs Eden AI](https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md)\n- [Claude API vs Simplismart](https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart.md)\n- [Antseed vs Simplismart](https://www.anchorterminal.com/compare/antseed-vs-simplismart.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 Simplismart](https://www.anchorterminal.com/compare/azure-openai-vs-simplismart.md)\n- [BlockRun.AI vs Eden AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.md)\n- [BlockRun.AI vs Simplismart](https://www.anchorterminal.com/compare/blockrun-ai-vs-simplismart.md)\n- [Cerebras Inference vs Eden AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.md)\n- [Cerebras Inference vs Simplismart](https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart.md)\n- [Cloudflare AI Gateway vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai.md)\n- [Cloudflare AI Gateway vs Simplismart](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-simplismart.md)\n- [Cloudflare Workers AI vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai.md)\n- [Cloudflare Workers AI vs Simplismart](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-simplismart.md)\n- [Cohere Chat API (Command models) vs Eden AI](https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai.md)\n- [Cohere Chat API (Command models) vs Simplismart](https://www.anchorterminal.com/compare/cohere-chat-vs-simplismart.md)\n- [DeepInfra vs Eden AI](https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai.md)\n- [DeepInfra vs Simplismart](https://www.anchorterminal.com/compare/deepinfra-vs-simplismart.md)\n- [DeepSeek API vs Eden AI](https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai.md)\n- [DeepSeek API vs Simplismart](https://www.anchorterminal.com/compare/deepseek-api-vs-simplismart.md)\n- [Eden AI vs Glimpse](https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse.md)\n- [Eden AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.md)\n- [Eden AI vs Gemini Developer API](https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api.md)\n- [Eden AI vs GroqCloud](https://www.anchorterminal.com/compare/eden-ai-vs-groq.md)\n- [Eden AI vs Inkling 2 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Simplismart](https://www.anchorterminal.com/compare/muse-spark-open-vs-simplismart.md)\n- [Novita AI vs Simplismart](https://www.anchorterminal.com/compare/novita-ai-vs-simplismart.md)\n- [OpenAI API vs Simplismart](https://www.anchorterminal.com/compare/openai-api-vs-simplismart.md)\n- [OpenRouter vs Simplismart](https://www.anchorterminal.com/compare/openrouter-vs-simplismart.md)\n- [Prism Inference vs Simplismart](https://www.anchorterminal.com/compare/prism-inference-vs-simplismart.md)\n- [Router.com (Ramp Router) vs Simplismart](https://www.anchorterminal.com/compare/ramp-router-vs-simplismart.md)\n- [Beam 1.0 vs Simplismart](https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.md)\n- [RouterPlus vs Simplismart](https://www.anchorterminal.com/compare/routerplus-vs-simplismart.md)\n- [SambaCloud vs Simplismart](https://www.anchorterminal.com/compare/sambanova-vs-simplismart.md)\n- [SiliconFlow vs Simplismart](https://www.anchorterminal.com/compare/siliconflow-vs-simplismart.md)\n- [Simplismart vs StepFun API](https://www.anchorterminal.com/compare/simplismart-vs-stepfun-api.md)\n- [Simplismart vs SWE-2 Flash](https://www.anchorterminal.com/compare/simplismart-vs-swe-2-flash.md)\n- [Simplismart vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub.md)\n- [Simplismart vs Together AI Inference](https://www.anchorterminal.com/compare/simplismart-vs-together-inference.md)\n- [Simplismart vs Vercel AI Gateway](https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway.md)\n- [Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.md)\n- [Simplismart vs xAI API (Grok)](https://www.anchorterminal.com/compare/simplismart-vs-xai-api.md)\n- [Antseed vs Eden AI](https://www.anchorterminal.com/compare/antseed-vs-eden-ai.md)\n- [Eden AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.md)\n- [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- [Nemotron 3.5 Super VL vs Simplismart](https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-simplismart.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 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