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hf-mcp-server packages MCP Server

@evalstate

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基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

evalstate

hf-mcp-server packages MCP Server について

Hugging Face MCP Server

hf-mcp-server packages MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "hf-mcp-server": {
      "command": "npx",
      "args": [
        "@llmindset/hf-mcp-server",
        "#",
        "Start",
        "in",
        "STDIO",
        "mode"
      ]
    }
  }
}

hf-mcp-server packages MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is hf-mcp-server?

hf-mcp-server is the official Hugging Face MCP server that connects LLMs to the Hugging Face Hub and thousands of Gradio AI applications. It provides MCP implementations of Hub API and search endpoints, enabling AI assistants to interact with Hugging Face resources.

How to use hf-mcp-server?

Install via one-click links for Claude Desktop/Web, VSCode, or Cursor, or use CLI commands for Claude Code (claude mcp add hf-mcp-server -t http https://huggingface.co/mcp?login) and Gemini CLI (gemini mcp add -t http huggingface https://huggingface.co/mcp?login). Run locally with npx @llmindset/hf-mcp-server (STDIO), npx @llmindset/hf-mcp-server-http (StreamableHTTP), or via Docker. Configure tokens via environment variables like DEFAULT_HF_TOKEN or HF_TOKEN.

Key features of hf-mcp-server

  • Supports STDIO, StreamableHTTP, and StreamableHTTP JSON transports
  • Web management interface on port 3000 for toggling tools
  • Proxy tools loaded from CSV-defined MCP endpoints
  • Skills directory support for shared Hugging Face skill catalogs
  • Stateful connection management with configurable timeouts
  • Environment variable configuration for timeouts, transport, and tool options

Use cases of hf-mcp-server

  • Connect an LLM to search and retrieve models, datasets, and Spaces from the Hugging Face Hub
  • Run Gradio AI applications directly through MCP tools
  • Build custom AI assistants that can interact with Hugging Face APIs
  • Deploy a local MCP server with proxy tools for internal workflows

よくある質問

1

What transports does hf-mcp-server support?

STDIO (stdin/stdout), StreamableHTTP (stateful HTTP with SSE), and StreamableHTTP JSON (stateless JSON-RPC mode).

2

How do I run hf-mcp-server locally?

Use `npx @llmindset/hf-mcp-server` for STDIO, `npx @llmindset/hf-mcp-server-http` for StreamableHTTP, or pull and run the Docker image from `ghcr.io/evalstate/hf-mcp-server:latest`.

3

How do I authenticate with the server?

Pass a Hugging Face token via the `Authorization: Bearer` header when configuring an MCP client, or set the `DEFAULT_HF_TOKEN` environment variable for development/STDIO use.

4

What environment variables control the server?

Key variables: `TRANSPORT` (transport mode), `DEFAULT_HF_TOKEN`, `HF_TOKEN` (STDIO fallback), `HF_API_TIMEOUT`, `ALLOW_INTERNAL_ADDRESS_HOSTS`, `MCP_STRICT_COMPLIANCE`, `AUTHENTICATE_TOOL`, `SEARCH_ENABLES_FETCH`, `PROXY_TOOLS_CSV`, `GRADIO_SKIP_INITIALIZE`, and `HF_SKILLS_DIR`.

5

Where can I manage tools after installation?

Navigate to https://huggingface.co/settings/mcp to configure your tools and Spaces. The local web dashboard on port 3000 also allows toggling tools.

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