{ "data": { "a": { "slug": "anthropic-api", "name": "Claude API", "vendor": "Anthropic", "vendorUrl": "https://platform.claude.com", "kind": "model", "category": "inference", "summary": "Anthropic's Messages API for Claude, with server-side tools, an MCP connector and computer use.", "url": "https://www.anchorterminal.com/tools/anthropic-api", "markdownUrl": "https://www.anchorterminal.com/tools/anthropic-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/anthropic-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/anthropic-api.json", "dns": "anthropic-api.grade.anchorterminal.com", "repo": "https://github.com/anthropics/anthropic-sdk-python", "license": "Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT)", "transports": [ "http" ], "remoteUrl": "https://api.anthropic.com/v1/messages", "packages": [ { "registry": "pypi", "name": "anthropic" }, { "registry": "npm", "name": "@anthropic-ai/sdk" } ], "auth": "api-key", "authNotes": "`Authorization: Bearer` header, with the legacy `x-api-key` header still accepted, plus `anthropic-version`. Personal and service-account keys are created in the Console for one workspace or several.", "pricing": "usage", "pricingNotes": "Prepaid credits. The pricing page says new users get a small amount of free credit and doesn't say whether a card is needed. Batch is half price. Cache writes cost 1.25x input for 5 minutes or 2x for an hour, reads 0.1x (0.05x on Opus 5.5 and Sonnet 5.5, 0.025x on Fable 5.1 and Mythos 5.1). Haiku 5.5 is priced by prompt length, $0.10/$0.50 per million up to 100,000 prompt tokens and $0.50/$2.50 above. US-only inference costs 1.1x. Fast mode on Opus 5.5 costs $8/$40 per million ($10/$50 on Opus 5 and 4.8, still in research preview; fast mode on Opus 4.8 is removed on 30 November 2026). Web search $10 per 1,000, web fetch billed as tokens only, code execution free alongside them or $0.05 per container hour after 1,550 free hours a month (https://platform.claude.com/docs/en/about-claude/pricing).", "priceSummary": "from $0.10 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Access needs a Console account with a card on file.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 3900, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://platform.claude.com/docs", "rateLimitsUrl": "https://platform.claude.com/docs/en/api/rate-limits", "llmsTxt": "https://platform.claude.com/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "card-required", "llms-txt" ], "lastRelease": "2026-10-30", "graded": true, "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.", "anchor": { "graded": true, "score": 77.3, "grade": "BB", "agentReady": true, "rank": 34, "ranked": true, "rankOf": 1486, "categoryRank": 6, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 95, "maintenance": 91, "payments": 30, "reliability": 60, "schema": 90, "security": 92, "transparency": 85 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.", "bestFor": "Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.", "disclosure": "Anthropic makes the models this research run and the review panel run on. This listing was graded by agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.", "strengths": [ "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model", "1M-token context on Opus 5.5, Sonnet 5.5 and Fable 5.1, with cache reads at $0.20 per million on Opus 5.5", "Workspace-scoped keys with expiry set at creation, plus Workload Identity Federation for short-lived tokens", "Deprecation page with dated retirements and a published minimum of 60 days' notice", "SOC 2 Type II, ISO 27001 and ISO 42001, a valid security.txt and a HackerOne programme" ], "weaknesses": [ "Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October", "Keys are created only in the browser Console, and there's no machine payment", "`tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5 and Fable 5.1, and thinking can't be disabled on Opus 5.5 or Fable 5.1", "Retention reads 'not retained by default' in the docs and 'deleted within 30 days' in the privacy centre", "No SLA on sale. Priority Tier's 99.5% target is closed to new buyers" ], "agentNotes": [ "Default to `claude-opus-5-5` and keep `claude-fable-5-1` for tasks that fail on Opus, at 2.5 times the price", "Don't send `tool_choice` any or tool to Opus 5.5, Sonnet 5.5 or Fable 5.1. Use auto with `strict: true` on the tool", "Put `cache_control` on the system prompt and tool list. Reads cost 0.05x input on Opus 5.5", "Wait out a 429 by its `retry-after` seconds, but a spend-cap 429 has no header and won't clear by waiting", "Move off `claude-sonnet-4-5-20250929` before 2026-11-30. Retired ids fail, they don't redirect", "Moving from `claude-haiku-4-5-20251001` to `claude-haiku-5-5`, drop temperature, top_p, top_k, prefill and `budget_tokens`, which return 400", "Pin your SDK major or `anthropic-version` deliberately. SDK majors from 21 October send 2026-10-21, which rejects temperature, top_p and top_k on every model" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 77.3 } ], "editorialScores": { "ergonomics": 95, "maintenance": 91, "payments": 30, "reliability": 60, "schema": 90, "security": 92, "transparency": 75 }, "provenanceScore": 95, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-10-08", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install anthropic # or: npm i @anthropic-ai/sdk", "http": "curl https://api.anthropic.com/v1/messages \\\n -H \"x-api-key: $ANTHROPIC_API_KEY\" -H \"anthropic-version: 2023-06-01\" \\\n -H \"content-type: application/json\" \\\n -d '{\"model\":\"claude-opus-5-5\",\"max_tokens\":512,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/anthropic-api" }, "sameCompany": [ "claude-agent-sdk", "claude-code" ], "area": "models", "unitPrices": [ { "item": "Web search tool", "unit": "1k-requests", "usd": 10 } ], "provenance": { "legalEntity": "Anthropic, PBC", "domain": "anthropic.com", "domainRegistered": "2001-10-02", "domainNote": "The API is on anthropic.com. anthropic.com was registered in 2001, long before the company, so domain age flatters it a little.", "endpointOnVendorDomain": true, "terms": "https://www.anthropic.com/legal/commercial-terms", "privacy": "https://www.anthropic.com/legal/privacy", "statusPage": "https://status.claude.com", "changelog": "https://platform.claude.com/docs/en/release-notes/overview", "securityTxt": "valid", "checked": "2026-11-01", "score": 95 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "unknown", "freeTier": true, "minutes": 5, "credential": "api-key", "hosting": [ "US", "global" ], "euResidency": "no", "trainsOnData": "no", "zeroRetention": "enterprise", "certifications": [ "HIPAA (BAA available)" ], "selfHost": "no" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/anthropic-api.json", "live": { "slug": "anthropic-api", "probe": { "target": "https://api.anthropic.com/v1/messages", "method": "get", "lastAt": "2026-11-07T18:20:10.465015097Z", "lastOk": true, "lastStatus": 405, "lastMs": 126, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 29, "p95ms24h": 111, "samples24h": 239, "samples30d": 7910, "days": [ { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "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": 187, "ok": 187 } ] }, "vendorStatus": { "page": "https://status.claude.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:20:32.746098278Z" }, "versions": [ { "registry": "github", "name": "anthropics/anthropic-sdk-python", "version": "v2.6.0", "released": "2026-11-05", "seenAt": "2026-11-06T23:06:18.426274609Z" }, { "registry": "npm", "name": "@anthropic-ai/sdk", "version": "1.6.0", "seenAt": "2026-11-06T23:06:18.048722321Z" }, { "registry": "pypi", "name": "anthropic", "version": "2.6.0", "released": "2026-11-05", "seenAt": "2026-11-06T23:06:17.932818075Z" } ], "githubStars": 4051, "npmWeekly": 66520800, "pypiWeekly": 50083571, "securityTxt": { "url": "https://anthropic.com/.well-known/security.txt", "state": "valid", "expires": "2026-12-31T23:59:00.000Z", "checkedAt": "2026-11-07T16:01:41.833331013Z" }, "llmsTxt": { "url": "https://platform.claude.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:33.576745074Z" }, "domain": { "domain": "anthropic.com", "registered": "2001-10-02", "source": "https://rdap.verisign.com/com/v1/domain/anthropic.com", "checkedAt": "2026-11-01T14:27:50.974079447Z" }, "pages": [ { "url": "https://platform.claude.com/docs/en/about-claude/model-deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:37.234784725Z", "changedAt": "2026-11-04T08:29:53.452957567Z", "fingerprint": "5edba16fbe22" }, { "url": "https://platform.claude.com/docs/en/api/migration-2026-10-21", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:41.50812183Z", "changedAt": "2026-11-05T12:39:30.640753951Z", "fingerprint": "6ea9f16badc0" }, { "url": "https://platform.claude.com/docs/en/build-with-claude/fast-mode", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:43.604513879Z", "changedAt": "2026-11-04T08:29:59.946000043Z", "fingerprint": "52f70ae31e3b" }, { "url": "https://platform.claude.com/docs/en/release-notes/overview", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:45.429427327Z", "changedAt": "2026-11-07T14:16:45.429427327Z", "fingerprint": "4eeb5247777c" }, { "url": "https://platform.claude.com/docs/en/about-claude/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:16:39.448205066Z", "changedAt": "2026-11-06T13:38:18.52721709Z", "fingerprint": "0aed66e62ce0" }, { "url": "https://www.anthropic.com/legal/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:24:51.866465684Z", "changedAt": "2026-11-06T13:45:59.405524922Z", "fingerprint": "607bc876aa3f" }, { "url": "https://www.anthropic.com/legal/commercial-terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:24:47.491480841Z", "changedAt": "2026-11-06T13:45:54.55551446Z", "fingerprint": "de97d1815b39" } ], "models": { "claude-fable-5-1": { "openrouterId": "anthropic/claude-fable-5.1", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "claude-haiku-4-5-20251001": { "openrouterId": "anthropic/claude-haiku-4.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 200000, "maxOutput": 64000, "checkedAt": "2026-10-10T22:59:28.614012396Z" }, "claude-haiku-5-5": { "openrouterId": "anthropic/claude-haiku-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "claude-opus-5-5": { "openrouterId": "anthropic/claude-opus-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "claude-sonnet-5": { "openrouterId": "anthropic/claude-sonnet-5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-10-01T21:56:15.532848159Z" }, "claude-sonnet-5-5": { "openrouterId": "anthropic/claude-sonnet-5.5", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "file", "image", "text" ], "promptCaching": true, "contextTokens": 1000000, "maxOutput": 128000, "checkedAt": "2026-11-06T23:49:25.225778715Z" } }, "github": { "repo": "anthropics/anthropic-sdk-python", "checkedAt": "2026-11-02T08:30:45.276257766Z", "stars": 4033, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-23T23:18:21Z", "openIssues": 72, "openPRs": 161, "issuesOpened90d": 68, "issuesClosed90d": 142, "prsMerged90d": 23, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-10-23T23:20:48Z" }, "advisories": [ { "ghsa": "GHSA-w828-4qhx-vxx3", "cve": "CVE-2026-34452", "severity": "medium", "published": "2026-03-31T17:53:42Z" }, { "ghsa": "GHSA-q5f5-3gjm-7mfm", "cve": "CVE-2026-34450", "severity": "medium", "published": "2026-03-31T17:53:28Z" } ], "replies": { "sampled": 25, "unanswered": 22, "medianDays": 9.2 } }, "updatedAt": "2026-11-07T18:20:10.465015097Z" } }, "answer": "Claude API scores 77.3 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.", "b": { "slug": "eden-ai", "name": "Eden AI", "vendor": "Eden AI SAS", "vendorUrl": "https://www.edenai.co", "kind": "router", "category": "inference", "summary": "Eden AI is a French AI gateway with one OpenAI-compatible API key for about 1,000 chat and expert models from 80 or more providers, including OCR, speech, translation and image analysis, with an EU-only endpoint and a hosted MCP server.", "url": "https://www.anchorterminal.com/tools/eden-ai", "markdownUrl": "https://www.anchorterminal.com/tools/eden-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/eden-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/eden-ai.json", "dns": "eden-ai.grade.anchorterminal.com", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://mcp.edenai.run/mcp", "packages": [], "auth": "api-key", "authNotes": "Bearer key created in the dashboard at app.edenai.run after a browser signup. Keys carry budgets, expiry and attribution, can be managed through a key API, and can be limited to chosen models by deny-by-default guardrails. The MCP server takes the same key in the Authorization header.", "pricing": "usage", "pricingNotes": "Provider list prices with no markup plus a 5.5% platform fee applied when buying credits. Prepaid credits through Stripe by card, PayPal or bank transfer, with optional auto-refill. Some models are billed $0 for tests. The Advanced plan is by quote.", "priceSummary": "5.5% fee", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in llms.txt, the OpenAPI spec, the pricing pages or the agent catalogue (checked 2026-11-06). Credits are bought through Stripe.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://www.edenai.co/docs", "llmsTxt": "https://www.edenai.co/llms.txt", "openapi": "https://api.edenai.run/v3/docs/openapi.json", "capabilities": [ "inference.router", "inference.llm", "embed.text", "translate.text", "translate.documents", "docs.ocr", "speech.stt", "speech.tts", "image.generate", "guard.moderation" ], "tags": [ "hosted", "router", "openai-compatible", "usage-priced", "prepaid", "mcp", "remote-mcp", "api-key", "llms-txt", "openapi", "eu", "eu-region", "soc2", "iso27001", "batch", "closed-source" ], "lastRelease": "2026-11-05", "graded": true, "anchor": { "graded": true, "score": 59.9, "grade": "C", "agentReady": false, "rank": 672, "ranked": true, "rankOf": 1486, "categoryRank": 22, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 58, "payments": 30, "reliability": 33, "schema": 81, "security": 82, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.", "bestFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.", "strengths": [ "OpenAI-compatible v3 API with an OpenAPI 3.1 spec and a keyless model catalogue with prices and regions", "EU endpoint that refuses models not cleared for European processing with HTTP 451", "Content isn't stored or used for training by default, with opt-in logs and enforceable Zero Data Retention", "Per-key budgets, expiry and deny-by-default guardrails, plus a key management API", "Hosted MCP server exposing OCR, speech, translation, web search and other expert models as tools" ], "weaknesses": [ "No public status page, incident history or SLA found", "The rate-limits page says 10 requests a second and the plans page says 7, raisable to 15", "No public changelog or deprecation policy", "The OpenAPI spec documents few error responses", "Credits are prepaid through Stripe with a 5.5% platform fee on every purchase" ], "agentNotes": [ "Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them", "Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed", "Set max_tokens to 500 or more for reasoning models, or the answer can come back empty", "Pass a fallbacks list so a provider 429 or error retries inside one request", "Poll check_job for MCP tools marked long-running instead of calling them again" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59.9 } ], "editorialScores": { "ergonomics": 75, "maintenance": 58, "payments": 30, "reliability": 33, "schema": 81, "security": 82, "transparency": 65 }, "provenanceScore": 44, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.edenai.run/v3/models", "claudeCode": "claude mcp add edenai --transport http https://mcp.edenai.run/mcp --header \"Authorization: Bearer $EDENAI_API_KEY\"", "config": { "mcpServers": { "edenai": { "headers": { "Authorization": "Bearer YOUR_EDENAI_API_KEY" }, "url": "https://mcp.edenai.run/mcp" } } } }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/eden-ai" }, "area": "models", "unitPrices": [ { "item": "Platform fee on credit purchases", "unit": "pct", "usd": 5.5, "note": "On top of provider list prices, which carry no markup" } ], "provenance": { "legalEntity": "Eden AI SAS", "domain": "edenai.co", "domainRegistered": "", "endpointOnVendorDomain": false, "terms": "https://www.edenai.co/terms", "privacy": "https://www.edenai.co/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The terms, last updated 22 October 2026, name Eden AI SAS, share capital €4,992, 19 rue Louis Guérin, 69100 Villeurbanne, France, under French law with courts in Lyon.", "The API and MCP server run on edenai.run, a second domain of the same company, while the site and docs are on edenai.co.", "robots.txt on www.edenai.co allows all agents and carries `Content-Signal: search=yes, ai-input=yes, ai-train=yes`.", "/.well-known/security.txt returns 404. No status page is linked, and status.edenai.co didn't resolve on 6 November 2026.", "RDAP for edenai.co wasn't read: rdap.org rate-limited us and the .co registry server wasn't tried." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/eden-ai.json", "live": { "slug": "eden-ai", "probe": { "target": "https://mcp.edenai.run/mcp", "method": "get", "lastAt": "2026-11-07T18:20:22.496540152Z", "lastOk": true, "lastStatus": 405, "lastMs": 123, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 50, "p95ms24h": 129, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "securityTxt": { "url": "https://edenai.co/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:41.694549385Z" }, "llmsTxt": { "url": "https://www.edenai.co/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:20.299431316Z" }, "pages": [ { "url": "https://www.edenai.co/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:28:13.706474894Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "21a1da47a2ce" }, { "url": "https://www.edenai.co/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:28:15.881335606Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "9cd0db8f0f61" } ], "mcpTools": { "url": "https://mcp.edenai.run/mcp", "checkedAt": "2026-11-07T01:44:01.27972989Z", "status": "ok", "protocol": "2025-11-25", "tools": [ { "name": "list_models", "description": "List available providers/models and their pricing.", "inputSchema": { "additionalProperties": false, "properties": { "tool": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Optional tool name (as returned by tools/list) to filter on." } }, "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "list_voices", "description": "List the voices a text-to-speech model accepts, for audio_tts's 'voice'.\n\nThe model's default voice comes first.", "inputSchema": { "additionalProperties": false, "properties": { "gender": { "anyOf": [ { "enum": [ "female", "male", "unknown" ], "type": "string" }, { "type": "null" } ], "default": null, "description": "Keep voices of this gender." }, "language": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Keep voices speaking this language: 'fr' matches every region,\n'fr-CA' only that locale. Multilingual voices are always kept." }, "limit": { "default": 50, "description": "Most voices to return (default 50, max 200); 'total' counts every match.", "type": "integer" }, "model": { "description": "The audio_tts model, as 'provider' or 'provider/model' (e.g. 'amazon/neural').", "type": "string" } }, "required": [ "model" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "upload_file", "description": "Upload a file to Eden AI and get a file ID to use in other tools.\n\nOnly needed for local file content. If you already have a public URL\nfor the file, pass that URL directly to the tool's file parameter\ninstead — no upload needed.", "inputSchema": { "additionalProperties": false, "properties": { "content_base64": { "description": "The file content, base64-encoded.", "type": "string" }, "expires_in_days": { "default": 30, "description": "How long Eden AI keeps the file (1-30, default 30).", "type": "integer" }, "filename": { "description": "Name with extension (used to detect the file type).", "type": "string" } }, "required": [ "content_base64", "filename" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "check_job", "description": "Get the status/result of an async job started by a long-running tool.", "inputSchema": { "additionalProperties": false, "properties": { "job_id": { "description": "The job id returned when the job was submitted.", "type": "string" } }, "required": [ "job_id" ], "type": "object" }, "outputSchema": { "additionalProperties": true, "type": "object" } }, { "name": "manage_collections", "description": "Create and manage collections: stored sets of items (e.g. faces) that a tool searches against. Tools that take a collection_id: image_face_recognition. Flow: create, then add_item once per file (returns the item ids it indexed), then call the tool with the collection_id; delete when done. Arguments per action: create(model, tool?, name?); list(tool?, model?, page?); get, delete, list_items(collection_id); add_item(collection_id, file); delete_item(collection_id, item_id).", "inputSchema": { "additionalProperties": false, "properties": { "action": { "enum": [ "create", "list", "get", "delete", "add_item", "list_items", "delete_item" ], "type": "string" }, "collection_id": { "description": "From create or list.", "type": "string" }, "file": { "description": "File to add (add_item). Pass a file ID (UUID) from upload_file, or a direct file URL.", "type": "string" }, "item_id": { "description": "Item to delete (delete_item), from add_item or list_items.", "type": "string" }, "model": { "description": "Provider the collection binds to (create; list filter). image_face_recognition: amazon.", "type": "string" }, "name": { "description": "Optional label (create).", "type": "string" }, "page": { "description": "Result page (list).", "minimum": 1, "type": "integer" }, "tool": { "description": "Tool the collection serves (create; list filter). Defaults to image_face_recognition.", "enum": [ "image_face_recognition" ], "type": "string" } }, "required": [ "action" ], "type": "object" } }, { "name": "audio_speech_to_text", "description": "Speech Recognition (or speech to text or voice to text) can recognize and transcribe spoken words (voice), that will be converted to text with or without diarization. It is also possible to filter profanity. The type of files allowed are: mp3, wav, m4a. If convert_to_wav option is set to true, then you can transcribe any type of audio or video files. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Audio file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: audio/*.", "type": "string" }, "language": { "description": "Language code in ISO format (e.g., 'en', 'fr', 'es')", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, assembly, deepgram, deepgram/base, deepgram/enhanced, deepgram/nova-3, gladia, google, gradium, gradium/stt-translate, greenpt, greenpt/green-s, greenpt/green-s-pro, microsoft, mistral, mistral/voxtral-mini-2602, mistral/voxtral-mini-latest, mistral/voxtral-mini-transcribe-3, mistral/voxtral-small-transcribe-3, openai. Call list_models for pricing.", "type": "string" }, "profanity_filter": { "default": false, "description": "Whether to filter profanity and replace inappropriate words with a series of asterisks", "type": "boolean" }, "speakers": { "default": 2, "description": "Number of speakers present in the audio", "minimum": 1, "type": "integer" }, "vocabulary": { "description": "List of words or composed words to be detected by the speech to text engine", "items": { "type": "string" }, "type": "array" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "audio_tts", "description": "Text-to-speech (TTS) is a technology that converts written text into spoken audio, enabling computers and digital devices to \"read\" text aloud. It is also known as speech synthesis, read aloud technology, or computer-generated speech.", "inputSchema": { "additionalProperties": false, "properties": { "audio_format": { "description": "Desired audio format (e.g., 'mp3', 'wav')", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon/neural, amazon/standard, deepgram/aura, deepgram/aura-2, elevenlabs, elevenlabs/eleven_flash_v2, elevenlabs/eleven_flash_v2_5, elevenlabs/eleven_multilingual_v2, elevenlabs/eleven_turbo_v2, elevenlabs/eleven_turbo_v2_5, elevenlabs/eleven_v3, google/casual, google/chirp-hd, google/chirp3-hd, google/gemini-2.5-flash-tts, google/gemini-2.5-pro-tts, google/gemini-3.1-flash-tts-preview, google/neural2, google/news, google/polyglot, google/standard, google/studio, google/wavenet, gradium, microsoft/neural, microsoft/neural-hd, mistral/voxtral-mini-tts-3, openai/gpt-4o-mini-tts, openai/tts-1, openai/tts-1-hd, ovhcloud/nvr-tts-de-de, ovhcloud/nvr-tts-en-us, ovhcloud/nvr-tts-es-es, ovhcloud/nvr-tts-it-it. Call list_models for pricing.", "type": "string" }, "speaking_pitch": { "description": "Increase or decrease the speaking pitch by a percentage from -100% to 100%, 0 is normal.", "maximum": 100, "minimum": -100, "type": "integer" }, "speaking_volume": { "description": "Increase or decrease the audio volume by a percentage from -100% to 100%, 0 is normal.", "maximum": 100, "minimum": -100, "type": "integer" }, "speed": { "description": "Speed multiplier for speech synthesis", "maximum": 4, "minimum": 0.25, "type": "number" }, "text": { "description": "Text to convert to speech", "minLength": 1, "type": "string" }, "voice": { "description": "Voice to synthesize with: an id or name from list_voices(model=...), matched case-insensitively. Omit it to use the model's default voice. An id the list doesn't know (e.g. your own cloned voice) is sent to the provider unchanged.", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "image_ai_detection", "description": "Determine whether an image was generated by AI or is a real photograph or artwork. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble, winstonai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_anonymization", "description": "Image Anonymization API, also known as image de-identification or image de-personalization, refers to the process of automatically removing personal or sensitive information from images. The main objective is to protect the privacy and security of individuals who may be depicted in images shared online or used for research purposes. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_background_removal", "description": "Background removal is a digital image processing technique designed to seamlessly eliminate the backdrop of a photo, leaving behind only the main subject. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai, clipdrop, photoroom, picsart, sentisight, stabilityai. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_deepfake_detection", "description": "Detect whether a face in a real photo has been swapped or manipulated (face-swap deepfakes). For fully AI-generated images, use AI Image Detection instead. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble, sightengine. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_explicit_content", "description": "Explicit Content Detection detects adult only content in images, that is generally inappropriate for people under the age of 18 and includes nudity, sexual activity, pornography, violence, gore content, etc. (type of files allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, google, microsoft, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_face_compare", "description": "Compare two faces and decide whether they are from the same person. The API expects 2 images, reference and query, where the former is the ground truth (e.g. user's official ID) and the latter is the validation image (e.g. a selfie). File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file1": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "file2": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, base64, facepp. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file1", "file2" ], "type": "object" } }, { "name": "image_face_detection", "description": "Face Detection is a computer technology being used in a variety of applications that identifies human faces in digital images with different attributes like landmarks, sentiments and physical attire (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_face_recognition", "description": "Recognizing a face in an image is a more advanced feature than just detecting the face in the image. It allows the user to search for the detected face from a database of existing images and extract the faces that are most similar to the face displayed in the query image. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "collection_id": { "description": "Id of one of your collections. Make one with manage_collections (action='create', then add_item for each file to search against); action='list' shows the ones you have. 'model' must be the collection's provider.", "type": "string" }, "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "collection_id", "file" ], "type": "object" } }, { "name": "image_generation", "description": "Image Generation is an advanced feature that generates compelling images based on a given text prompt. It can easily produce high-quality and original images in a matter of seconds, without the need for specialized design skills or software File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "mask": { "description": "Optional inpainting mask. Must be paired with at least one reference image (otherwise the request returns 422). Support varies by model; models that do not accept a mask surface the error as status=\"fail\" with a provider message in the response body. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: bytedance, bytedance/seedream-4-0-250828, bytedance/seedream-4-5-251128, bytedance/seedream-5-0-260128, google, google/gemini-2.5-flash-image, google/gemini-3-pro-image-preview, infomaniak/flux, ionos/black-forest-labs/FLUX.1-schnell, ionos/black-forest-labs/FLUX.2-klein-4B, leonardo, leonardo/AlbedoBase XL, leonardo/Leonardo Anime XL, leonardo/Leonardo Diffusion XL, leonardo/Leonardo Kino XL, leonardo/Leonardo Lightning XL, leonardo/Leonardo Phoenix, leonardo/Leonardo Vision XL, leonardo/SDXL 0.9, minimax, minimax/image-01, openai, openai/gpt-image-1, openai/gpt-image-1-mini, openai/gpt-image-1.5, openai/gpt-image-2, ovhcloud/stable-diffusion-xl-base-v10, pruna/p-image, pruna/p-image-edit, pruna/p-image-ideogram, pruna/p-image-ideogram-low, pruna/p-image-ideogram-medium, pruna/p-image-ideogram-very-high, pruna/p-image-ideogram-very-low, replicate, replicate/anime-style, replicate/classic, replicate/vintedois-diffusion, stabilityai, stabilityai/stable-diffusion-xl-1024-v1-0. Call list_models for pricing.", "type": "string" }, "num_images": { "default": 1, "description": "Number of images to generate", "maximum": 10, "minimum": 1, "type": "integer" }, "reference_images": { "description": "Optional reference images. Plain file IDs/URLs are treated as ReferenceImage with kind=None. Support and per-model limits vary by model; models that do not accept reference images surface the error as status=\"fail\" with a provider message in the response body.", "items": {}, "maxItems": 64, "type": "array" }, "resolution": { "description": "Image resolution as a named size (e.g. '1024x1024'). Optional: providers may also accept native sizing knobs (width/height, aspect_ratio, image_size tier, etc.) in the top-level `provider_params` request field, next to `input` rather than inside it, in which case `provider_params` takes precedence.", "pattern": "^\\d+x\\d+$", "type": "string" }, "text": { "description": "Text prompt for image generation", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "image_logo_detection", "description": "Logo Detection is a powerful technology that enables the automatic identification and recognition of popular logos within an image. It provides accurate and efficient detection of known (and less known) brand logos. It's a valuable tool for a variety of industries, including advertising, retail, and e-commerce. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: api4ai, api4ai/v1, api4ai/v2, google, microsoft, openai, openai/gpt-4-turbo, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "image_object_detection", "description": "Object Detection is a computer vision technique that allows users to identify and locate (with bounding boxes) objects in an image. The detected objects can be animals, people, electronics, vehicles etc. (type of file allowed: jpg, jpeg, png, tiff) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, microsoft, sentisight. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr", "description": "Optical Character Recognition or Reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text. The image can be a scanned document or a photo of a license plate, a road sign or anything else that contains text (type of files allowed: jpg, jpeg, png, tiff) . File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "language": { "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, api4ai, google, ionos, ionos/lightonai/LightOnOCR-2-1B, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest, sentisight. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_async", "description": "OCR or Optical Character Recognition is also referred to as text recognition or text extraction. It allows users to extract text data from PDFs with multiple pages. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, microsoft, mistral, mistral/mistral-ocr-2512, mistral/mistral-ocr-3, mistral/mistral-ocr-3-0, mistral/mistral-ocr-4, mistral/mistral-ocr-4-0, mistral/mistral-ocr-4-1, mistral/mistral-ocr-latest. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_financial_parser", "description": "Financial Parser API is a powerful and versatile tool designed to streamline your financial data extraction process. This cutting-edge API combines Optical Character Recognition (OCR) technology with advanced parsing capabilities to seamlessly extract and organize relevant information from invoices and receipts. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "document_type": { "default": "invoice", "description": "Specify the type of your document. Can be set to 'auto-detect' for automatic detection if the provider supports it.", "enum": [ "auto-detect", "invoice", "receipt" ], "type": "string" }, "file": { "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.", "type": "string" }, "language": { "description": "Document language code. Most providers detect the language themselves and ignore this field; providers that cannot detect it reject requests that omit it. Check the provider's supported languages before relying on it.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, eagledoc, extracta, google, klippa, microsoft, mindee, openai, openai/gpt-4o, tabscanner, veryfi. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_identity_parser", "description": "ID Document parsing technology allows users to automatically extract information from an ID Document such as passport, ID card, driving license and more. This API is ideal for developers looking to create applications that require identity verification or access control. It extracts information like name, date of birth, nationality, age and more. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, amazon, base64, klippa, microsoft, mindee, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_resume_parser", "description": "Resume Parser enables users to extract various information from resumes (curriculum vitae, CV) that could be in a variety of formats and returns structured data (name, job list, education, skills) to automate their processing. (type of files allowed: pdf, jpg, jpeg, png) File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "File ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/*, application/*, text/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: affinda, extracta, klippa, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "ocr_tables", "description": "OCR Table (Optical Character Recognition for tabular documents) allows users to analyze documents containing tables and returns a structured representation of the detected tables in the form of a Json object that can be converted to a CSV. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "PDF or image file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, image/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, google, microsoft. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "text_ai_detection", "description": "The AI Detection API is a tool designed to determine whether a given text was generated by an artificial intelligence chatbot, or a Language Model (LLM).", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: sapling, winstonai. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for AI detection, at least 300 characters long. Shorter texts carry too little signal to be scored reliably.", "minLength": 300, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_anonymization", "description": "The personally identifiable information (PII) detection feature can identify and redact sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Removing these personally identifiable information helps with the Anonymization of a text and privacy protection.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, limina, microsoft. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to detect personal information in", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_moderation", "description": "Text moderation scans text for offensive, sexually explicit or suggestive content, it also checks if there is any content of self-harm, violence, racist or hate speech.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: google, microsoft, openai, openai/text-moderation-007, openai/text-moderation-latest, openai/text-moderation-stable, ovhcloud/Qwen3Guard-Gen-0.6B, ovhcloud/Qwen3Guard-Gen-8B. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to moderate", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_named_entity_recognition", "description": "Named Entity Recognition (also called entity identification or extraction) is an information extraction technique that automatically identifies named entities in a text and classifies them into predefined categories such as dates, persons names, company names, dates, products etc.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: amazon, microsoft, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for named entities", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_plagia_detection", "description": "The Plagiarism Detection API is a tool designed to scan a content string for plagiarism using a plagiarism detection module", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: winstonai. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text content on which plagiarism detection will be run", "minLength": 1, "type": "string" }, "title": { "description": "Content title", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_spell_check", "description": "Spell Check analyzes the inputted text by comparing it to a dictionary of correctly spelled words to identify and highlight any spelling errors or grammatical mistakes.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: prowritingaid, sapling. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to be spell-checked", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "text_topic_extraction", "description": "Topic analysis is a Natural Language Processing (NLP) technique that allows us to automatically extract meaning from text by identifying recurrent themes or topics.", "inputSchema": { "additionalProperties": false, "properties": { "language": { "description": "ISO 639-1 language code", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: google, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "text": { "description": "Text to analyze for topics", "minLength": 1, "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "translation_automatic_translation", "description": "Automatic translation or machine translation (MT) is the process of automatically translating a text from one language to another language. The aim of it is to enable people to communicate and access information in different languages, without the need for a human translator.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: amazon, deepl, google, microsoft, modernmt, openai, openai/gpt-4o. Call list_models for pricing.", "type": "string" }, "source_language": { "description": "Source language code", "minLength": 1, "type": "string" }, "target_language": { "description": "Target language code", "minLength": 1, "type": "string" }, "text": { "description": "Text to translate", "minLength": 1, "type": "string" } }, "required": [ "model", "text", "target_language" ], "type": "object" } }, { "name": "translation_document_translation", "description": "Document Translation API translates whole documents in supported languages and various file formats (like pdf or doc) while keeping their structure intact. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Document file ID from /v3/upload or direct file URL (PDF, DOCX, PPTX) Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/vnd.openxmlformats-officedocument.presentationml.presentation.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: deepl, google. Call list_models for pricing.", "type": "string" }, "source_language": { "description": "Source language code", "minLength": 1, "type": "string" }, "target_language": { "description": "Target language code", "minLength": 1, "type": "string" } }, "required": [ "model", "file", "target_language" ], "type": "object" } }, { "name": "video_deepfake_detection", "description": "Detect deepfake and synthetically manipulated video. Returns an overall deepfake score and prediction, along with per-frame scores when the provider supplies them. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "file": { "description": "Video file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: resemble. Call list_models for pricing.", "type": "string" } }, "required": [ "model", "file" ], "type": "object" } }, { "name": "video_generation", "description": "The Video Generation API enables easy creation of high-quality videos from text,and images, perfect for marketing, education, and more—all through one integration. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'. File parameters accept a file ID from upload_file or a direct file URL — if you already have a URL, pass it as-is (no upload needed).", "inputSchema": { "additionalProperties": false, "properties": { "dimension": { "default": "1280x720", "description": "Video resolution in 'widthxheight' format (e.g., '1280x720')", "pattern": "^\\d+x\\d+$", "type": "string" }, "duration": { "description": "Length of the generated video in seconds. Omit to use the model's default duration.", "maximum": 120, "minimum": 1, "type": "integer" }, "file": { "description": "Initial keyframe image (JPEG or PNG) file ID from /v3/upload or direct file URL Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: image/jpeg, image/png.", "type": "string" }, "model": { "description": "Which provider/model to run, exactly one of: bytedance, bytedance/dreamina-seedance-2-0-260128, bytedance/dreamina-seedance-2-0-fast-260128, bytedance/dreamina-seedance-2-0-mini-260615, bytedance/dreamina-seedance-2-5-260628, bytedance/seedance-1-0-pro-250528, bytedance/seedance-1-0-pro-fast-251015, bytedance/seedance-1-5-pro-251215, minimax, minimax/MiniMax-Hailuo-02, minimax/MiniMax-Hailuo-2.3, minimax/S2V-01, minimax/T2V/I2V-01-Director, openai, openai/sora-2, openai/sora-2-pro, pixverse, pixverse/c1, pixverse/v5, pixverse/v5.5, pixverse/v6, pruna, pruna/p-video, pruna/p-video-2, pruna/p-video-2-pro, pruna/p-video-2-pro-cost, pruna/p-video-2-pro-quality, pruna/p-video-animate, pruna/p-video-avatar, pruna/p-video-edit, xai/grok-imagine-video-1.5, xai/grok-imagine-video-1.5-lite. Call list_models for pricing.", "type": "string" }, "seed": { "description": "Random seed for generation reproducibility (0 to 2,147,483,646). Omit for varied output.", "maximum": 2147483646, "minimum": 0, "type": "integer" }, "text": { "description": "Text prompt describing the content and style of the video to generate", "minLength": 1, "type": "string" }, "video": { "description": "Source video to edit, for models that edit a video (their `requires_video` is true in /v3/info). The output keeps the source's length, which is what is billed, so `duration` and `dimension` do not apply to them. Other models refuse it. Pass a file ID (UUID) from upload_file, or a direct file URL. Accepted types: video/*.", "type": "string" } }, "required": [ "model", "text" ], "type": "object" } }, { "name": "web_batch_scrape", "description": "Scrape many URLs in one request and return each page's content. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.", "type": "string" }, "urls": { "description": "Explicit list of URLs to scrape (async job)", "items": { "type": "string" }, "minItems": 1, "type": "array" } }, "required": [ "model", "urls" ], "type": "object" } }, { "name": "web_crawl", "description": "Crawl a site from a starting URL and return the content of its pages. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "Root URL to crawl (async job)", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_map", "description": "Discover and return the list of URLs on a site (a sitemap-style link map).", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "Root URL to map (discover its links)", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_research", "description": "Run deep, multi-step web research on a query and return a synthesized answer with sources. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl, linkup, tavily. Call list_models for pricing.", "type": "string" }, "prompt": { "description": "Natural-language research task for the agent", "minLength": 1, "type": "string" }, "reasoning_depth": { "default": "L", "description": "Research reasoning-effort tier (billed per tier; priced pre-call)", "enum": [ "S", "M", "L", "XL" ], "type": "string" }, "schema": { "description": "JSON schema describing the structured output", "type": "object" } }, "required": [ "model", "prompt" ], "type": "object" } }, { "name": "web_scraping", "description": "Fetch a single URL and return its clean content as markdown, text, or HTML, with optional JavaScript rendering.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, tavily. Call list_models for pricing.", "type": "string" }, "url": { "description": "URL of the web page to scrape", "minLength": 1, "type": "string" } }, "required": [ "model", "url" ], "type": "object" } }, { "name": "web_search", "description": "Search the web for a query and return ranked results (title, URL, and a snippet or the page content).", "inputSchema": { "additionalProperties": false, "properties": { "depth": { "default": "standard", "description": "Search depth tier. `deep` is refused with a 400 on deepseek, perplexityai and zai, which run one tier only.", "enum": [ "standard", "deep" ], "type": "string" }, "max_results": { "description": "Max number of search results to return", "minimum": 1, "type": "integer" }, "model": { "description": "Which provider/model to run, exactly one of: deepseek, firecrawl, linkup, perplexityai, tavily, zai. Call list_models for pricing.", "type": "string" }, "query": { "description": "The web search query", "minLength": 1, "type": "string" } }, "required": [ "model", "query" ], "type": "object" } }, { "name": "web_structured_extraction", "description": "Extract structured data from one or more web pages against a schema or prompt. Runs as an async job. Long-running: returns a job immediately; poll it with check_job(job_id) every few seconds until status is 'success' or 'fail'.", "inputSchema": { "additionalProperties": false, "properties": { "model": { "description": "Which provider/model to run, exactly one of: firecrawl. Call list_models for pricing.", "type": "string" }, "prompt": { "description": "Natural-language description of what to extract", "type": "string" }, "schema": { "description": "JSON schema describing the structured output", "type": "object" }, "urls": { "description": "URLs to extract structured data from (async job)", "items": { "type": "string" }, "minItems": 1, "type": "array" } }, "required": [ "model", "urls" ], "type": "object" } } ], "schemaTokens": 10725, "changedAt": "2026-11-07T01:44:01.27972989Z", "check": { "checker": "anchor-check/1.0", "totalTokens": 10725, "counts": { "error": 0, "note": 1, "warn": 49 }, "findings": [ { "rule": "TC11", "severity": "warn", "tool": "manage_collections", "message": "1 parameter without a description: action", "fix": "Describe each one: format, units, an example, and what happens when it's left out." }, { "rule": "TC12", "severity": "warn", "tool": "image_generation", "message": "no type for reference_images[]", "fix": "Give every parameter a type (or an enum)." }, { "rule": "TC13", "severity": "warn", "tool": "web_research", "message": "schema (object with no properties)", "fix": "Declare the properties (or additionalProperties with a schema) and the array's items." }, { "rule": "TC13", "severity": "warn", "tool": "web_structured_extraction", "message": "schema (object with no properties)", "fix": "Declare the properties (or additionalProperties with a schema) and the array's items." }, { "rule": "TC14", "severity": "warn", "tool": "image_face_recognition", "message": "allowed values are in the description, not an enum: collection_id", "fix": "Move them into enum." }, { "rule": "TC14", "severity": "warn", "tool": "image_generation", "message": "allowed values are in the description, not an enum: resolution", "fix": "Move them into enum." }, { "rule": "TC16", "severity": "warn", "tool": "audio_speech_to_text", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "audio_tts", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "check_job", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "image_ai_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_anonymization", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_background_removal", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_deepfake_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_explicit_content", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_compare", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_face_recognition", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_generation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_logo_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "image_object_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "list_models", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "list_voices", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"list\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "manage_collections", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_async", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_financial_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_identity_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_resume_parser", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "ocr_tables", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_ai_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_anonymization", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_moderation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_named_entity_recognition", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_plagia_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "text_spell_check", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"check\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "text_topic_extraction", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "translation_automatic_translation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "translation_document_translation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "upload_file", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "video_deepfake_detection", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "video_generation", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_batch_scrape", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_crawl", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_map", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_research", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_scraping", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC16", "severity": "warn", "tool": "web_search", "message": "no readOnlyHint or destructiveHint", "fix": "Its name starts with \"search\"; if it only reads, set readOnlyHint: true so harnesses can run it without asking." }, { "rule": "TC16", "severity": "warn", "tool": "web_structured_extraction", "message": "no readOnlyHint or destructiveHint", "fix": "Set readOnlyHint: true if it only reads; otherwise set destructiveHint and idempotentHint." }, { "rule": "TC23", "severity": "warn", "message": "42 tools", "fix": "Offer a smaller default toolset and let clients opt into the rest." }, { "rule": "TC24", "severity": "note", "message": "38 of 42 tools have no outputSchema", "fix": "Declare outputSchema for tools that return structured data, and return structuredContent that matches it." } ] } }, "updatedAt": "2026-11-07T18:20:22.496540152Z" } }, "edges": [ { "by": 33, "category": "maintenance", "leads": "anthropic-api", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. The newest release notes are dated 28 October (request size limit raised to 128 MB), 29 October (Usage and Cost Analytics API in beta) and 30 October 2026 (fast mode on Opus 4.8 deprecated, removal on 30 November) (30). Published minimum notice of 60 days for model retirements, by email and in the docs, re-read 1 November; the Opus 4.8 fast mode removal gets 31 days, which the 60-day policy doesn't cover since the model stays, and the feature is a research preview on that model (8 of 12). One model shutdown date in the last 90 days, Opus 4.1 on 5 August, kept to its notice (8 of 8). Dated release notes several times a week and a support centre (15 of 15). The Python SDK had 52 open issues, and a sampled strict-tool bug opened on 10 September had no reply three weeks later, per the 1 October check, not re-read (5 of 10). Current official SDKs, Python `anthropic` 2.3.0 and TypeScript `sdk-v1.3.0`, both tagged 23 October, after new major versions (Python 2.0.0, TypeScript 1.0.0) on 21 October that send API version 2026-10-21 by default (15). Supported runtimes stated, Python 3.10 to 3.14 (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.", "b": "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." }, "scores": { "a": 91, "b": 58 } }, { "by": 30, "category": "transparency", "leads": "anthropic-api", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service with clear commercial terms (effective 17 June 2025, re-read 1 November, with Anthropic Ireland, Limited as the contracting party for customers in the EEA, Switzerland and the UK and Anthropic, PBC elsewhere, per the 15 October check). The SDKs moved from MIT to Apache 2.0 with the major versions of 21 October, both OSI licences (15). The privacy policy is effective 10 September 2026, re-read 1 November. Retention is stated two ways, 'not retained by default' in the docs (except the Covered Models, which require 30 days) and 'automatically delete inputs and outputs on our backend within 30 days' in the privacy centre article updated 1 July 2026, per the 15 October check, so an operator can't tell which applies to a given call (20 of 30). Deprecation page with announcement and retirement dates (20). Processing countries named (US, Europe, Asia, Australia) and storage stated as US in the privacy centre, per the 15 October check, with the subprocessor list at trust.anthropic.com per the 1 October check (20). 15 + 20 + 20 + 20 = 75.", "b": "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." }, "scores": { "a": 85, "b": 55 } }, { "by": 27, "category": "reliability", "leads": "anthropic-api", "name": "Reliability", "reasons": { "a": "Status page at status.claude.com with component history (20). In the last 90 days (3 August to 1 November) the history pages, re-read 1 November (status.claude.com's robots.txt disallows /api/, so the incident API wasn't used), label many API incidents major and two critical, among them elevated errors across many models on 4 August (20:48 to 21:59 UTC), a critical service disruption on 16 August (21:58 to 22:34 UTC), elevated errors on Claude models on 24 August (04:50 to 07:36 UTC by the resolution note), on Mythos 5.1, Fable 5.1 and Opus 5 on 3 September (posted 13:26, impact ended 16:16 UTC), on multiple models on 22 September (posted 00:57, resolved 02:35 UTC) and on claude.ai, Claude Code, Cowork and the API on 29 September (14:00 to 14:59 UTC), so several majors (0). Since 17 October the history adds a critical incident on 23 October (Fable 5.1, Sonnet 5.5, Haiku 5.5 and fast mode on Opus 5.5, 23:28 to 23:59 UTC), and majors on Opus 5.5 on 24 October (00:31 to 00:37 UTC), Fable 5 and 5.1 on 24 October (05:16 to 05:53 UTC), Sonnet 5.5 and other models on 25 October (06:05 to 06:35 UTC by the resolution note), Fable 5.1 on 25 October (08:17 to 08:49 UTC) and Sonnet 5.5 twice on 27 October (09:14 to 09:56 and 15:09 to 15:50 UTC). The 21 and 29 July incidents left the window. Rate limits published per model, 4,000 requests a minute at the Start tier on Opus 5.5, Sonnet 5.5, Haiku 5.5 and Fable 5.x and 1,000 on older models, re-read 1 November (15). 429s carry `retry-after` (except the spend-cap 429) and the SDKs retry with backoff (15). No SLA on sale. Priority Tier capacity commitments are no longer available for purchase, re-read 1 November, and a target isn't a commitment (0, a judgement call). Messages API is GA (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by agents running on Claude, by the same checklist as every other listing.", "b": "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." }, "scores": { "a": 60, "b": 33 } }, { "by": 20, "category": "ergonomics", "leads": "anthropic-api", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5, Fable 5.1 and Mythos 5.1, re-read 1 November, so a tool can't be forced on the larger current models. Structured outputs GA (15). Prompt caching with reads at 0.1x input, 0.05x on Opus 5.5 and Sonnet 5.5 and 0.025x on Fable 5.1 and Mythos 5.1 (15). 1M context on the default model (15). Batch at half price (10). Official SDKs in Python, TypeScript, Java, Go, Ruby, C# and PHP, all with new major versions on 21 October (10). Documented error types, `retry-after` and SDK retries with backoff (15). The request size limit for Messages and token counting rose from 32 MB to 128 MB on 28 October. 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.", "b": "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." }, "scores": { "a": 95, "b": 75 } }, { "by": 10, "category": "security", "leads": "anthropic-api", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Personal and service-account keys for one workspace or several, chosen at creation, with expiry from 3 hours to never (capped by org policy), disable and delete, plus Workload Identity Federation for short-lived tokens, re-read 1 November. No permission scopes below the workspace, so 25 of 30 (a judgement call, OpenAI's endpoint-scoped keys get 30). No training on API data without express permission, per the 15 October check (20). Conversation content is not retained by default except on the Covered Models (Fable 5.1, Mythos 5.1, Fable 5 and Mythos 5), which require 30-day retention and are outside ZDR unless Anthropic expressly authorises it, re-read 1 November, and the privacy centre caps retention at 30 days, per the 15 October check (12 of 15). Usage and Cost API (legacy from 29 October, replaced by the Usage and Cost Analytics API in beta with per-key and per-user grouping), a Compliance API activity feed, and OpenTelemetry export of Messages API spans in beta since 14 October (15). security.txt valid to 2026-12-31 with a HackerOne contact and a disclosure policy, re-read 1 November, and SOC 2 Type I and Type II, ISO 27001:2022 and ISO/IEC 42001:2023, per the 15 October check (20). 25 + 20 + 12 + 15 + 20 = 92.", "b": "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." }, "scores": { "a": 92, "b": 82 } }, { "by": 9, "category": "schema", "leads": "anthropic-api", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI document in the docs. The Python SDK repository bundles a Stainless-generated OpenAPI 3.1 file (`scripts/mock-spec.json.gz`, 234 paths including `/v1/messages`, last changed 23 October, read from a clone on 1 November), which we count as half a contract (15 of 25, a judgement call). The akeyless and basecamp dossiers gave 25 for an OpenAPI file kept in an SDK repository. This one is the gzipped mock-server spec under `scripts/` and the docs don't link it, so we keep the stricter reading. llms.txt indexes 845 pages, each with a Markdown twin, re-read 1 November (10). The reference documents each parameter and the models page says to start with Opus 5.5 for most workloads (20). Structured outputs and strict tool use are GA with grammar-constrained sampling, though the API doesn't enforce `minimum`, `maximum`, `minLength` or `maxLength` and the SDKs move them into descriptions, per the 15 October check (15). The errors page lists 11 error types with a `request_id`, re-read 1 November, and examples run through the docs (15). `anthropic-version` header, with a second version, 2026-10-21, released on 21 October beside 2023-06-01 and documented with a migration guide, and dated release notes with an RSS feed, newest 30 October (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.", "b": "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." }, "scores": { "a": 90, "b": 81 } } ], "facts": [ { "a": "Model API", "b": "Model router", "name": "Kind" }, { "a": "Anthropic", "b": "Eden AI SAS", "name": "Vendor" }, { "a": "https://api.anthropic.com/v1/messages", "b": "https://mcp.edenai.run/mcp", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable 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": "Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT)", "b": "none", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-11-05", "name": "Last release" }, { "a": "no date given", "b": "2026-10-22", "name": "Terms last updated" }, { "a": "no date given", "b": "2026-10-22", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "3.9k stars", "b": "none", "name": "Popularity" }, { "a": "3.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Claude API scores 77.3 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Claude API or Eden AI?" }, { "answer": "Both need an API key.", "question": "Do Claude API and Eden AI need an API key?" }, { "answer": "Yes. Claude API has a hosted endpoint at https://api.anthropic.com/v1/messages and Eden AI at https://mcp.edenai.run/mcp.", "question": "Can an agent call Claude API and Eden AI without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 60 against 33", "Schema \u0026 documentation, 90 against 81", "Agent ergonomics, 95 against 75", "Security \u0026 auth, 92 against 82", "Maintenance \u0026 community, 91 against 58", "Transparency \u0026 trust, 85 against 55" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.", "slug": "anthropic-api", "watchFor": "Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October" }, { "aheadOn": null, "also": null, "goodFor": "Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.", "slug": "eden-ai", "watchFor": "No public status page, incident history or SLA found" } ], "history": { "anthropic-api": [ { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.3, "from": 77.6, "fromGrade": "BB", "to": 77.3, "toGrade": "BB" } ], "eden-ai": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.json", "title": "Amazon Bedrock vs Claude API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api" }, { "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/anthropic-api-vs-antseed.json", "title": "Claude API vs Antseed", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-antseed" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.json", "title": "Claude API vs Azure OpenAI in Foundry Models", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.json", "title": "Claude API vs BlockRun.AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.json", "title": "Claude API vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway.json", "title": "Claude API vs Cloudflare AI Gateway", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai.json", "title": "Claude API vs Cloudflare Workers AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.json", "title": "Claude API vs Cohere Chat API (Command models)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra.json", "title": "Claude API vs DeepInfra", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.json", "title": "Claude API vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse.json", "title": "Claude API vs Glimpse", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.json", "title": "Claude API vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.json", "title": "Claude API vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq.json", "title": "Claude API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.json", "title": "Claude API vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.json", "title": "Claude API vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.json", "title": "Claude API vs Jais 3", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json", "title": "Claude API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.json", "title": "Claude API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.json", "title": "Claude API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.json", "title": "Claude API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl.json", "title": "Claude API vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.json", "title": "Claude API vs Novita AI", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.json", "title": "Claude API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter.json", "title": "Claude API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.json", "title": "Claude API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router.json", "title": "Claude API vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.json", "title": "Claude API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus.json", "title": "Claude API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.json", "title": "Claude API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.json", "title": "Claude API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow" }, { "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/anthropic-api-vs-stepfun-api.json", "title": "Claude API vs StepFun API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash.json", "title": "Claude API vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.json", "title": "Claude API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.json", "title": "Claude API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.json", "title": "Claude API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.json", "title": "Claude API vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.json", "title": "Claude API vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/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/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/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/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-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/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/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/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/eden-ai-vs-elorian-glimpse.json", "title": "Eden AI vs Glimpse", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-elorian-glimpse" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.json", "title": "Eden AI vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api.json", "title": "Eden AI vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-groq.json", "title": "Eden AI vs GroqCloud", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.json", "title": "Eden AI vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.json", "title": "Eden AI vs Jais 3", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.json", "title": "Eden AI vs Meta Model API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api.json", "title": "Eden AI vs MiniMax API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api.json", "title": "Eden AI vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.json", "title": "Eden AI vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl.json", "title": "Eden AI vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.json", "title": "Eden AI vs Novita AI", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.json", "title": "Eden AI vs OpenAI API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference.json", "title": "Eden AI vs Prism Inference", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.json", "title": "Eden AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.json", "title": "Eden AI vs SambaCloud", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.json", "title": "Eden AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.json", "title": "Eden AI vs Simplismart", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.json", "title": "Eden AI vs StepFun API", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash.json", "title": "Eden AI vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.json", "title": "Eden AI vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.json", "title": "Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api.json", "title": "Eden AI vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai.json", "title": "Antseed vs Eden AI", "url": "https://www.anchorterminal.com/compare/antseed-vs-eden-ai" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.json", "title": "Eden AI vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm.json", "title": "Eden AI vs LiteLLM", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-litellm" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter.json", "title": "Eden AI vs OpenRouter", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router.json", "title": "Eden AI vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus.json", "title": "Eden AI vs RouterPlus", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub.json", "title": "Eden AI vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway.json", "title": "Eden AI vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-vercel-ai-gateway" } ], "panel": null, "scores": [ { "anthropic-api": 60, "by": 27, "eden-ai": 33, "edge": "anthropic-api", "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "anthropic-api": 90, "by": 9, "eden-ai": 81, "edge": "anthropic-api", "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "anthropic-api": 95, "by": 20, "eden-ai": 75, "edge": "anthropic-api", "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "anthropic-api": 92, "by": 10, "eden-ai": 82, "edge": "anthropic-api", "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "anthropic-api": 30, "by": 0, "eden-ai": 30, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "anthropic-api": 91, "by": 33, "eden-ai": 58, "edge": "anthropic-api", "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "anthropic-api": 85, "by": 30, "eden-ai": 55, "edge": "anthropic-api", "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Claude API scores 77.3 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "anthropic-api": "Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai", "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.min.md" }, "markdown": "Claude API scores 77.3 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Claude API: grade BB, 77.3/100, rank #34 of 1486. Markdown https://www.anchorterminal.com/tools/anthropic-api.md · JSON https://www.anchorterminal.com/api/v1/tools/anthropic-api.json\n- Eden AI: grade C, 59.9/100, rank #672 of 1486. Markdown https://www.anchorterminal.com/tools/eden-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n- 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### Claude API (BB)\n\nGood for: Long agent loops that lean on tool use, strict schemas and caching, and teams that want 1M context at Opus or Sonnet prices.\n\nAhead on:\n- Reliability, 60 against 33\n- Schema \u0026 documentation, 90 against 81\n- Agent ergonomics, 95 against 75\n- Security \u0026 auth, 92 against 82\n- Maintenance \u0026 community, 91 against 58\n- Transparency \u0026 trust, 85 against 55\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Many API incidents labelled major in the 90 days to 1 November 2026, among them a critical one on 23 October and five more from 24 to 27 October\n\n### Eden AI (C)\n\nGood for: Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.\n\nWatch for: No public status page, incident history or SLA found\n\n\n## Why the edge\n\n### Maintenance \u0026 community: Claude API +33\n\n- Claude API (91): Model reading. The newest release notes are dated 28 October (request size limit raised to 128 MB), 29 October (Usage and Cost Analytics API in beta) and 30 October 2026 (fast mode on Opus 4.8 deprecated, removal on 30 November) (30). Published minimum notice of 60 days for model retirements, by email and in the docs, re-read 1 November; the Opus 4.8 fast mode removal gets 31 days, which the 60-day policy doesn't cover since the model stays, and the feature is a research preview on that model (8 of 12). One model shutdown date in the last 90 days, Opus 4.1 on 5 August, kept to its notice (8 of 8). Dated release notes several times a week and a support centre (15 of 15). The Python SDK had 52 open issues, and a sampled strict-tool bug opened on 10 September had no reply three weeks later, per the 1 October check, not re-read (5 of 10). Current official SDKs, Python `anthropic` 2.3.0 and TypeScript `sdk-v1.3.0`, both tagged 23 October, after new major versions (Python 2.0.0, TypeScript 1.0.0) on 21 October that send API version 2026-10-21 by default (15). Supported runtimes stated, Python 3.10 to 3.14 (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.\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\n### Transparency \u0026 trust: Claude API +30\n\n- Claude API (85): Closed service with clear commercial terms (effective 17 June 2025, re-read 1 November, with Anthropic Ireland, Limited as the contracting party for customers in the EEA, Switzerland and the UK and Anthropic, PBC elsewhere, per the 15 October check). The SDKs moved from MIT to Apache 2.0 with the major versions of 21 October, both OSI licences (15). The privacy policy is effective 10 September 2026, re-read 1 November. Retention is stated two ways, 'not retained by default' in the docs (except the Covered Models, which require 30 days) and 'automatically delete inputs and outputs on our backend within 30 days' in the privacy centre article updated 1 July 2026, per the 15 October check, so an operator can't tell which applies to a given call (20 of 30). Deprecation page with announcement and retirement dates (20). Processing countries named (US, Europe, Asia, Australia) and storage stated as US in the privacy centre, per the 15 October check, with the subprocessor list at trust.anthropic.com per the 1 October check (20). 15 + 20 + 20 + 20 = 75.\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\n### Reliability: Claude API +27\n\n- Claude API (60): Status page at status.claude.com with component history (20). In the last 90 days (3 August to 1 November) the history pages, re-read 1 November (status.claude.com's robots.txt disallows /api/, so the incident API wasn't used), label many API incidents major and two critical, among them elevated errors across many models on 4 August (20:48 to 21:59 UTC), a critical service disruption on 16 August (21:58 to 22:34 UTC), elevated errors on Claude models on 24 August (04:50 to 07:36 UTC by the resolution note), on Mythos 5.1, Fable 5.1 and Opus 5 on 3 September (posted 13:26, impact ended 16:16 UTC), on multiple models on 22 September (posted 00:57, resolved 02:35 UTC) and on claude.ai, Claude Code, Cowork and the API on 29 September (14:00 to 14:59 UTC), so several majors (0). Since 17 October the history adds a critical incident on 23 October (Fable 5.1, Sonnet 5.5, Haiku 5.5 and fast mode on Opus 5.5, 23:28 to 23:59 UTC), and majors on Opus 5.5 on 24 October (00:31 to 00:37 UTC), Fable 5 and 5.1 on 24 October (05:16 to 05:53 UTC), Sonnet 5.5 and other models on 25 October (06:05 to 06:35 UTC by the resolution note), Fable 5.1 on 25 October (08:17 to 08:49 UTC) and Sonnet 5.5 twice on 27 October (09:14 to 09:56 and 15:09 to 15:50 UTC). The 21 and 29 July incidents left the window. Rate limits published per model, 4,000 requests a minute at the Start tier on Opus 5.5, Sonnet 5.5, Haiku 5.5 and Fable 5.x and 1,000 on older models, re-read 1 November (15). 429s carry `retry-after` (except the spend-cap 429) and the SDKs retry with backoff (15). No SLA on sale. Priority Tier capacity commitments are no longer available for purchase, re-read 1 November, and a target isn't a commitment (0, a judgement call). Messages API is GA (10). 20 + 0 + 15 + 15 + 0 + 10 = 60. Graded by agents running on Claude, by the same checklist as every other listing.\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\n### Agent ergonomics: Claude API +20\n\n- Claude API (95): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns 400 on Opus 5.5, Sonnet 5.5, Fable 5.1 and Mythos 5.1, re-read 1 November, so a tool can't be forced on the larger current models. Structured outputs GA (15). Prompt caching with reads at 0.1x input, 0.05x on Opus 5.5 and Sonnet 5.5 and 0.025x on Fable 5.1 and Mythos 5.1 (15). 1M context on the default model (15). Batch at half price (10). Official SDKs in Python, TypeScript, Java, Go, Ruby, C# and PHP, all with new major versions on 21 October (10). Documented error types, `retry-after` and SDK retries with backoff (15). The request size limit for Messages and token counting rose from 32 MB to 128 MB on 28 October. 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.\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\n### Security \u0026 auth: Claude API +10\n\n- Claude API (92): Model reading. Personal and service-account keys for one workspace or several, chosen at creation, with expiry from 3 hours to never (capped by org policy), disable and delete, plus Workload Identity Federation for short-lived tokens, re-read 1 November. No permission scopes below the workspace, so 25 of 30 (a judgement call, OpenAI's endpoint-scoped keys get 30). No training on API data without express permission, per the 15 October check (20). Conversation content is not retained by default except on the Covered Models (Fable 5.1, Mythos 5.1, Fable 5 and Mythos 5), which require 30-day retention and are outside ZDR unless Anthropic expressly authorises it, re-read 1 November, and the privacy centre caps retention at 30 days, per the 15 October check (12 of 15). Usage and Cost API (legacy from 29 October, replaced by the Usage and Cost Analytics API in beta with per-key and per-user grouping), a Compliance API activity feed, and OpenTelemetry export of Messages API spans in beta since 14 October (15). security.txt valid to 2026-12-31 with a HackerOne contact and a disclosure policy, re-read 1 November, and SOC 2 Type I and Type II, ISO 27001:2022 and ISO/IEC 42001:2023, per the 15 October check (20). 25 + 20 + 12 + 15 + 20 = 92.\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\n### Schema \u0026 documentation: Claude API +9\n\n- Claude API (90): No OpenAPI document in the docs. The Python SDK repository bundles a Stainless-generated OpenAPI 3.1 file (`scripts/mock-spec.json.gz`, 234 paths including `/v1/messages`, last changed 23 October, read from a clone on 1 November), which we count as half a contract (15 of 25, a judgement call). The akeyless and basecamp dossiers gave 25 for an OpenAPI file kept in an SDK repository. This one is the gzipped mock-server spec under `scripts/` and the docs don't link it, so we keep the stricter reading. llms.txt indexes 845 pages, each with a Markdown twin, re-read 1 November (10). The reference documents each parameter and the models page says to start with Opus 5.5 for most workloads (20). Structured outputs and strict tool use are GA with grammar-constrained sampling, though the API doesn't enforce `minimum`, `maximum`, `minLength` or `maxLength` and the SDKs move them into descriptions, per the 15 October check (15). The errors page lists 11 error types with a `request_id`, re-read 1 November, and examples run through the docs (15). `anthropic-version` header, with a second version, 2026-10-21, released on 21 October beside 2023-06-01 and documented with a migration guide, and dated release notes with an RSS feed, newest 30 October (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.\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\n## Score by category\n\n| Category | Weight | Claude API | Eden AI | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 60 | 33 | Claude API +27 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 90 | 81 | Claude API +9 |\n| Agent ergonomics | 13% (16.2 this run) | 95 | 75 | Claude API +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 92 | 82 | Claude API +10 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 30 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 91 | 58 | Claude API +33 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 55 | Claude API +30 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **77.3 · BB** | **59.9 · C** | |\n\n## Facts side by side\n\n| Fact | Claude API | Eden AI |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Anthropic | Eden AI SAS |\n| Hosted endpoint | `https://api.anthropic.com/v1/messages` | `https://mcp.edenai.run/mcp` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Apache 2.0 (SDKs from the 21 October 2026 major versions; earlier versions MIT) | none |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-11-05 |\n| Terms last updated | no date given | 2026-10-22 |\n| Privacy policy last updated | no date given | 2026-10-22 |\n| Customer content may train models | yes, with an opt-out | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | yes | not found in the text |\n| Popularity | 3.9k stars | none |\n| Agent reviews | 3.5/5 (4) | none |\n\n## How the scores have moved\n\n### Claude API\n\n- -0.3 on 8 October 2026: checklist\n\n### Eden AI\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Claude API.** Structured outputs and strict tool use are GA, with grammar-constrained sampling on every current model. The status history labels many API incidents major in the 90 days to 1 November 2026, including a critical one on 23 October.\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## Before you call either\n\n### Claude API\n\n1. Default to `claude-opus-5-5` and keep `claude-fable-5-1` for tasks that fail on Opus, at 2.5 times the price\n2. Don't send `tool_choice` any or tool to Opus 5.5, Sonnet 5.5 or Fable 5.1. Use auto with `strict: true` on the tool\n3. Put `cache_control` on the system prompt and tool list. Reads cost 0.05x input on Opus 5.5\n4. Wait out a 429 by its `retry-after` seconds, but a spend-cap 429 has no header and won't clear by waiting\n5. Move off `claude-sonnet-4-5-20250929` before 2026-11-30. Retired ids fail, they don't redirect\n6. Moving from `claude-haiku-4-5-20251001` to `claude-haiku-5-5`, drop temperature, top_p, top_k, prefill and `budget_tokens`, which return 400\n7. Pin your SDK major or `anthropic-version` deliberately. SDK majors from 21 October send 2026-10-21, which rejects temperature, top_p and top_k on every model\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## Questions\n\n### Which is better for AI agents, Claude API or Eden AI?\n\nClaude API scores 77.3 (BB) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories.\n\n### Do Claude API and Eden AI need an API key?\n\nBoth need an API key.\n\n### Can an agent call Claude API and Eden AI without installing anything?\n\nYes. Claude API has a hosted endpoint at https://api.anthropic.com/v1/messages and Eden AI at https://mcp.edenai.run/mcp.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"anthropic-api\", \"b\": \"eden-ai\"}`. From a terminal: `anchor compare anthropic-api eden-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/anthropic-api.json and https://www.anchorterminal.com/api/v1/tools/eden-ai.json\n\n## Other comparisons with Claude API or Eden AI\n\n- [Amazon Bedrock vs Claude API](https://www.anchorterminal.com/compare/amazon-bedrock-vs-anthropic-api.md)\n- [Amazon Bedrock vs Eden AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-eden-ai.md)\n- [Claude API vs Antseed](https://www.anchorterminal.com/compare/anthropic-api-vs-antseed.md)\n- [Claude API vs Azure OpenAI in Foundry Models](https://www.anchorterminal.com/compare/anthropic-api-vs-azure-openai.md)\n- [Claude API vs BlockRun.AI](https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.md)\n- [Claude API vs Cerebras Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.md)\n- [Claude API vs Cloudflare AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-ai-gateway.md)\n- [Claude API vs Cloudflare Workers AI](https://www.anchorterminal.com/compare/anthropic-api-vs-cloudflare-workers-ai.md)\n- [Claude API vs Cohere Chat API (Command models)](https://www.anchorterminal.com/compare/anthropic-api-vs-cohere-chat.md)\n- [Claude API vs DeepInfra](https://www.anchorterminal.com/compare/anthropic-api-vs-deepinfra.md)\n- [Claude API vs DeepSeek API](https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.md)\n- [Claude API vs Glimpse](https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse.md)\n- [Claude API vs Fireworks AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.md)\n- [Claude API vs Gemini Developer API](https://www.anchorterminal.com/compare/anthropic-api-vs-gemini-api.md)\n- [Claude API vs GroqCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-groq.md)\n- [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md)\n- [Claude API vs Inkling 2 Small](https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.md)\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Claude API vs MiniMax API](https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.md)\n- [Claude API vs Mistral AI API](https://www.anchorterminal.com/compare/anthropic-api-vs-mistral-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Claude API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/anthropic-api-vs-nemotron-3-5-super-vl.md)\n- [Claude API vs Novita AI](https://www.anchorterminal.com/compare/anthropic-api-vs-novita-ai.md)\n- [Claude API vs OpenAI API](https://www.anchorterminal.com/compare/anthropic-api-vs-openai-api.md)\n- [Claude API vs OpenRouter](https://www.anchorterminal.com/compare/anthropic-api-vs-openrouter.md)\n- [Claude API vs Prism Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-prism-inference.md)\n- [Claude API vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/anthropic-api-vs-ramp-router.md)\n- [Claude API vs Beam 1.0](https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.md)\n- [Claude API vs RouterPlus](https://www.anchorterminal.com/compare/anthropic-api-vs-routerplus.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Claude API vs SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Claude API vs Simplismart](https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart.md)\n- [Claude API vs StepFun API](https://www.anchorterminal.com/compare/anthropic-api-vs-stepfun-api.md)\n- [Claude API vs SWE-2 Flash](https://www.anchorterminal.com/compare/anthropic-api-vs-swe-2-flash.md)\n- [Claude API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.md)\n- [Claude API vs Together AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-together-inference.md)\n- [Claude API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/anthropic-api-vs-vercel-ai-gateway.md)\n- [Claude API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/anthropic-api-vs-vertex-ai.md)\n- [Claude API vs xAI API (Grok)](https://www.anchorterminal.com/compare/anthropic-api-vs-xai-api.md)\n- [Azure OpenAI in Foundry Models vs Eden AI](https://www.anchorterminal.com/compare/azure-openai-vs-eden-ai.md)\n- [BlockRun.AI vs Eden AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.md)\n- [Cerebras Inference vs Eden AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.md)\n- [Cloudflare AI Gateway vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-eden-ai.md)\n- [Cloudflare Workers AI vs Eden AI](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-eden-ai.md)\n- [Cohere Chat API (Command models) vs Eden AI](https://www.anchorterminal.com/compare/cohere-chat-vs-eden-ai.md)\n- [DeepInfra vs Eden AI](https://www.anchorterminal.com/compare/deepinfra-vs-eden-ai.md)\n- [DeepSeek API vs Eden AI](https://www.anchorterminal.com/compare/deepseek-api-vs-eden-ai.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 Small](https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.md)\n- [Eden AI vs Jais 3](https://www.anchorterminal.com/compare/eden-ai-vs-jais-3.md)\n- [Eden AI vs Meta Model API](https://www.anchorterminal.com/compare/eden-ai-vs-meta-model-api.md)\n- [Eden AI vs MiniMax API](https://www.anchorterminal.com/compare/eden-ai-vs-minimax-api.md)\n- [Eden AI vs Mistral AI API](https://www.anchorterminal.com/compare/eden-ai-vs-mistral-api.md)\n- [Eden AI vs Muse Spark Open](https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.md)\n- [Eden AI vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/eden-ai-vs-nemotron-3-5-super-vl.md)\n- [Eden AI vs Novita AI](https://www.anchorterminal.com/compare/eden-ai-vs-novita-ai.md)\n- [Eden AI vs OpenAI API](https://www.anchorterminal.com/compare/eden-ai-vs-openai-api.md)\n- [Eden AI vs Prism Inference](https://www.anchorterminal.com/compare/eden-ai-vs-prism-inference.md)\n- [Eden AI vs Beam 1.0](https://www.anchorterminal.com/compare/eden-ai-vs-reflection-beam.md)\n- [Eden AI vs SambaCloud](https://www.anchorterminal.com/compare/eden-ai-vs-sambanova.md)\n- [Eden AI vs SiliconFlow](https://www.anchorterminal.com/compare/eden-ai-vs-siliconflow.md)\n- [Eden AI vs Simplismart](https://www.anchorterminal.com/compare/eden-ai-vs-simplismart.md)\n- [Eden AI vs StepFun API](https://www.anchorterminal.com/compare/eden-ai-vs-stepfun-api.md)\n- [Eden AI vs SWE-2 Flash](https://www.anchorterminal.com/compare/eden-ai-vs-swe-2-flash.md)\n- [Eden AI vs Together AI Inference](https://www.anchorterminal.com/compare/eden-ai-vs-together-inference.md)\n- [Eden AI vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/eden-ai-vs-vertex-ai.md)\n- [Eden AI vs xAI API (Grok)](https://www.anchorterminal.com/compare/eden-ai-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\n## Disclosure\n\n- Anthropic makes the models this research run and the review panel run on. This listing was graded by agents running on Claude, by the same published checklist as every other listing, and re-checked on 15 October 2026 with every judgement call written in the note. Since that date the panel reviews it too, at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Claude API vs Eden AI", "url": "" } ], "description": "Claude scores 77.3 (BB) to Eden AI's 59.9 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Claude API BB 77.3", "Eden AI C 59.9", "scores" ], "h1": "Claude API vs Eden AI", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/anthropic-api-vs-eden-ai", "published": "2026-10-01", "section": "tools", "title": "Claude vs Eden AI for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-eden-ai" }, "tokens": { "markdown": 7000, "slim": 3630 }, "version": 1 }