🤗 Hugging Face MCP Server 🤗

Name: 🤗 Hugging Face MCP Server 🤗
Author: shreyaskarnik

@shreyaskarnik

代码仓库

关于 🤗 Hugging Face MCP Server 🤗

暂无概览

基本信息

分类

AI 与智能体

许可证

MIT

运行时

python

传输方式

stdio

发布者

shreyaskarnik

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "huggingface-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "@shreyaskarnik/huggingface-mcp-server",
        "--client",
        "claude"
      ]
    }
  }
}

工具

Search models with filters for query, author, tags, and limit

Get detailed information about a specific model

Search datasets with filters

Get detailed information about a specific dataset

Search Spaces with filters including SDK type

Get detailed information about a specific Space

Get information about a paper and its implementations

Get the list of curated daily papers

Search collections with various filters

Get detailed information about a specific collection

概览

What is Hugging Face MCP Server?

A Model Context Protocol (MCP) server that provides read-only access to the Hugging Face Hub APIs. It allows LLMs like Claude to interact with Hugging Face's models, datasets, spaces, papers, and collections.

How to use Hugging Face MCP Server?

Install via Smithery or configure the server in Claude Desktop’s claude_desktop_config.json using uv run huggingface_mcp_server.py. Set the optional HF_TOKEN environment variable for higher rate limits and private repository access. After installation, use the provided prompts and tools to query the Hub.

Key features of Hugging Face MCP Server

Custom hf:// URI scheme for models, datasets, and spaces
Prompts: compare models and summarize research papers
Tools to search and get info on models, datasets, spaces, papers, and collections
Optional Hugging Face authentication via HF_TOKEN
No required configuration; works out-of-the-box

Use cases of Hugging Face MCP Server

Search for models or datasets by query, author, or tags
Compare multiple Hugging Face models side by side
Summarize a research paper using its arXiv ID
Retrieve the list of curated daily papers
Explore collections and their contents

FAQ from Hugging Face MCP Server

What is the `HF_TOKEN` environment variable used for?

It is optional. Setting it provides higher API rate limits and access to private repositories (if authorized). It also improves reliability for high-volume requests.

How do I debug the server?

Use the MCP Inspector by running npx @modelcontextprotocol/inspector uv --directory /path/to/huggingface-mcp-server run huggingface_mcp_server.py. Server logs are stored in ~/Library/Logs/Claude/mcp-server-huggingface.log (macOS) or %APPDATA%\Claude\logs\mcp-server-huggingface.log (Windows).

How do I install for Claude Desktop?

You can install automatically via Smithery with npx -y @smithery/cli install @shreyaskarnik/huggingface-mcp-server --client claude, or manually add the configuration to claude_desktop_config.json under mcpServers.

What resources does the server expose?

It exposes models (hf://model/{model_id}), datasets (hf://dataset/{dataset_id}), spaces (hf://space/{space_id}), and daily papers and collections via tools. All resources have descriptive names and JSON content type.