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Hugging FaceMCP Server
by Hugging Face
Released
v0.4.10
MIT
Summary
Hugging Face's official remote MCP server — search and inspect models, datasets and Spaces, browse the Hub filesystem over hf:// URIs, and turn Gradio Spaces into callable tools.
Features
- hub_repo_search: one query interface across models, datasets and Spaces
- hub_repo_details: metadata for one or more repos with type auto-detection
- hf_fs: ls/cat/find/stat/search over hf:// URIs across the whole Hub
- hf_whoami: inspect the active account, orgs and credential scope
- Expose chosen Gradio Spaces as generated, callable tools
- OAuth (?login) or HF token auth; anonymous access is rate-limited
- Self-hostable over stdio or stateless streamable HTTP via npx or Docker
Installation
Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.
Description
The Hugging Face MCP server puts the Hub itself inside an agent. Point a client at https://huggingface.co/mcp and the model stops guessing which checkpoint exists: it can search models, datasets and Spaces through one query interface, pull details for specific repos, and read files straight out of a repo without you downloading anything first.
The built-in tools (what an anonymous connection sees today, at server version 0.4.10):
hub_repo_search— one search surface across models, datasets and Spaces, or aggregated across all three.hub_repo_details— full metadata for one or more repos, with the type auto-detected.hf_fs— a filesystem over the Hub:ls,cat,find,stat,attachand search againsthf://URIs, rooted at models, datasets, Spaces and buckets.hf_whoami— which account and organisations the current credential can see, useful for debugging a permissions problem before blaming the tool.
Gradio Spaces as tools. The interesting part is what you add to that. At huggingface.co/settings/mcp you choose which Spaces to expose, and the server generates tool aliases for them — so an image model, a transcription demo or any other Gradio app running on the Hub becomes something the agent can call directly. That is how one endpoint turns into thousands of task-specific tools without any of them being packaged or shipped.
Connecting. It is a remote streamable-HTTP server. Use https://huggingface.co/mcp?login for a browser OAuth flow, or https://huggingface.co/mcp with an Authorization: Bearer hf_... header for a token. Anonymous use works but is rate-limited, and the server says so in its own instructions. Claude Code, Claude Desktop and claude.ai (via the connector gallery), Cursor, VS Code, Gemini CLI and any other MCP client with HTTP transport are supported. You can also self-host it — npx @llmindset/hf-mcp-server for stdio, or the ghcr.io/evalstate/hf-mcp-server image for stateless streamable HTTP — which is the route to take if you need DISABLE_TOOLS, host allowlists or your own metrics dashboard.
MIT licensed, and the reference implementation is developed in the open.
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