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Hugging Face

Hugging Face

by Hugging Face
v0.4.6
MIT
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huggingfacemodelsdatasetsgradioresearchofficial

Summary

Official Hugging Face MCP server: search models, datasets, Spaces and papers on the Hub, read repository files, and call Gradio apps as agent tools.

Features

  • Semantic search across Hub models, datasets and Spaces
  • Search and read machine-learning papers indexed on the Hub
  • Browse and read files inside any Hub repository
  • Call public Gradio Spaces as MCP tools
  • Hosted Streamable HTTP endpoint with OAuth or HF_TOKEN auth
  • Self-hostable via Docker in stdio or HTTP mode
  • Per-user tool selection to keep the exposed tool list small

Installation

Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.

Any MCP-compatible agent

Most agents (Claude, Cursor, Windsurf, VS Code, and more) read a standard mcpServers configuration.

  1. Open your agent's MCP configuration file.
  2. Merge the snippet below into it.
  3. Restart the agent — the "Hugging Face" tools will be available.
{
  "mcpServers": {
    "huggingface-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://huggingface.co/mcp?login"
      ]
    }
  }
}

Description

The Hugging Face MCP Server is the vendor-maintained bridge between an MCP client and the Hugging Face Hub. Instead of pasting model cards into a prompt, an agent can query the Hub directly — searching models, datasets, Spaces and research papers, then pulling the exact files it needs out of a repository through the built-in filesystem tool.

The second half of the server is what makes it unusual: Hugging Face Spaces built with Gradio expose themselves as MCP tools, so any of the thousands of public Gradio applications on the Hub — image generation, transcription, OCR, background removal — become callable functions for your agent without you writing an integration for each one.

The hosted endpoint at https://huggingface.co/mcp is the fastest route: Claude Code, Claude Desktop, VS Code, Cursor and Gemini CLI all connect over Streamable HTTP, with OAuth login or a personal HF_TOKEN bearer header. The same TypeScript server can be self-hosted from source or the published Docker image, in either stdio or stateless HTTP mode, which is the practical choice when you need to restrict the toolset (DISABLE_TOOLS) or point the server at an internal deployment.

Useful details: the server is MIT-licensed and published as hf-mcp; token-free anonymous access works for public read operations, while anything touching your own repos or private Spaces needs a token; and per-user tool selection ("bouquets") keeps the tool list small enough not to crowd out the rest of your agent's tools.

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