{"data":{"_id":"69b2da6867df398baec12ea9","name":"Hugging Face","slug":"hugging-face","url":"https://huggingface.co","description":"","logo":"","category":"AI & ML","tags":[],"pricingModel":"unknown","scores":{"tokenEfficiency":{"score":8,"confidence":"scanner","evidence":"OpenAPI spec with 151 endpoints supports field selection and pagination, plus batch endpoints for efficient bulk operations, though response verbosity details are unknown.","na":false},"access":{"score":8,"confidence":"scanner","evidence":"Comprehensive REST API (151 endpoints) with official SDKs in Node.js and Python, plus integrations with major frameworks (Vercel AI SDK, ActivePieces), but lacking MCP server support limits agent interoperability.","na":false},"auth":{"score":9,"confidence":"scanner","evidence":"API key authentication enables autonomous agent operation without human intervention, with no mention of restrictive OAuth requirements or complex permission scoping needs.","na":false},"speed":{"score":6,"confidence":"scanner","evidence":"Batch endpoints and pagination support enable efficient throughput, but response time metrics are unavailable and rate limits are not documented in the collected signals.","na":false},"discoverability":{"score":9,"confidence":"scanner","evidence":"Complete OpenAPI specification available at well-known endpoint with 151 documented endpoints, developer docs present, and no apparent discovery blockers.","na":false},"reliability":{"score":6,"confidence":"scanner","evidence":"OpenAPI spec suggests consistent API structure, but signals lack evidence of idempotency keys, API versioning, response schema stability, or status page monitoring.","na":false},"safety":{"score":5,"confidence":"scanner","evidence":"API key authentication provides some access control, but no explicit evidence of sandbox/test mode, dry-run capabilities, or fine-grained scoped tokens for limiting agent permissions.","na":false},"reactivity":{"score":4,"confidence":"scanner","evidence":"No mention of webhooks, streaming, Server-Sent Events, or other real-time notification mechanisms in the collected signals.","na":false}},"agentGrade":"B+","agentScore":7.44,"accessMethods":{"restApi":true,"graphql":false,"cli":false,"sdk":["Node (@huggingface/inference)","Python (huggingface)"],"mcpServer":"none","openApiSpec":"https://huggingface.co/.well-known/openapi.json","llmsTxt":false,"agentsJson":false},"authInfo":{"methods":["api_key"],"scopedPermissions":false,"humanRequired":false},"reviewCount":0,"avgReviewScore":0,"viewCount":51,"badgeEmbedCount":15,"agentSkillSlugs":[],"alternatives":[],"claimed":false,"status":"graded","createdAt":"2026-03-12T15:23:20.706Z","updatedAt":"2026-04-09T04:16:46.250Z","__v":0,"scannerData":{"lastScannedAt":"2026-03-12T19:35:45.319Z","scanVersion":1,"rawSignals":{"homepage":{"status":200,"contentLength":145558,"hasStructuredData":false,"hasDeveloperDocs":true,"hasAgentMentions":true,"responseTimeMs":null},"openapi":{"found":true,"specUrl":"https://huggingface.co/.well-known/openapi.json","endpointCount":151,"hasFieldSelection":true,"hasPagination":true,"hasBatchEndpoints":true,"authMethods":["api_key"]},"wellKnown":{"llmsTxt":{"found":false},"agentsJson":{"found":false},"robotsTxt":{"found":true,"blocksAgents":false,"hasSitemap":true}},"packages":{"npm":[{"name":"@huggingface/inference","description":"Typescript client for the Hugging Face Inference Providers and Inference Endpoints","version":"4.13.15"},{"name":"@huggingface/hub","description":"Utilities to interact with the Hugging Face hub","version":"2.11.0"},{"name":"@theia/ai-huggingface","description":"Theia - Hugging Face Integration","version":"1.69.0"},{"name":"@logto/connector-huggingface","description":"Hugging Face connector implementation.","version":"0.4.3"},{"name":"@huggingface/space-header","description":"Use the Space mini_header outside Hugging Face","version":"1.0.4"},{"name":"@huggingface/jinja","description":"A minimalistic JavaScript implementation of the Jinja templating engine, specifically designed for parsing and rendering ML chat templates.","version":"0.5.6"},{"name":"@ai-sdk/huggingface","description":"The **[Hugging Face Inference Providers](https://huggingface.co/docs/inference-providers/index)** for the [Vercel AI SDK](https://ai-sdk.dev/docs) contains language model support for thousands of models through multiple inference providers via the Hugging","version":"1.0.37"},{"name":"@activepieces/piece-hugging-face","description":"This library was generated with [Nx](https://nx.dev).","version":"0.1.3"}],"pypi":[{"name":"huggingface","version":"0.0.1","description":"HuggingFace is a single library comprising the main HuggingFace libraries."}],"cli":false,"sdks":["Node (@huggingface/inference)","Python (huggingface)"]},"mcp":{"found":false,"type":"none","servers":[]}},"biggestFriction":"Absence of MCP server support and lack of real-time reactivity features (webhooks/streaming) limit agent framework interoperability and event-driven automation capabilities.","agentSummary":"Hugging Face offers excellent programmatic access through a comprehensive REST API with strong discoverability via OpenAPI specs and multi-language SDKs, making it well-suited for agent integration. However, the lack of MCP support, missing safety guardrails (sandbox/test mode), and no real-time reactivity features leave room for improvement in modern agent-native tooling."}}}