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PyPI MCP Server

PyPI MCP Server

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github.com/JackKuo666Developer Tools2Updated 82w ago

About PyPI MCP Server

PyPI MCP Server connects AI assistants to PyPI for Python package searches and access to metadata, releases, and download statistics. It communicates with MCP clients over standard input/output.

Key features

  1. 01Search packages by keyword
  2. 02Retrieve package metadata
  3. 03View released versions
  4. 04Get download statistics

Use cases

  1. 01Find Python packages for a task
  2. 02Check a package's version history
  3. 03Review package download statistics

MCP support

This MCP server exposes PyPI package search, metadata, release, and download-statistics tools to MCP clients over standard input/output.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

PyPI MCP Server

🔍 Enabling AI assistants to search and access PyPI package information through a simple MCP interface.

PyPI MCP Server provides a bridge to the PyPI package repository for AI assistants through the Model Context Protocol (MCP). It allows AI models to programmatically search Python packages and access their metadata, supporting features like retrieving package information, searching packages, viewing version history, and download statistics.

✨ Core Features

  • 🔎 Package Search: Query PyPI packages by keywords ✅
  • 📊 Metadata Access: Get detailed metadata for specific packages ✅
  • 📦 Version Information: Get all released versions of a package ✅
  • 📈 Statistics Data: Get download statistics for packages ✅
  • 🚀 Efficient Retrieval: Fast access to package information ✅

🚀 Quick Start

Prerequisites
  • Python 3.10+
  • httpx
  • BeautifulSoup4
  • mcp-python-sdk
  • typing-extensions
Installation
  1. Clone the repository:

    git clone https://github.com/JackKuo666/PyPI-MCP-Server.git
    cd PyPI-MCP-Server
    
  2. Install required dependencies:

    pip install -r requirements.txt
    
Running the Server
python pypi_server.py

The server will communicate with MCP clients through standard input/output (stdio).

📚 MCP Tools

Get Package Information
get_package_info(package_name: str, version: Optional[str] = None) -> Dict

Get detailed information about a specified package, with optional version specification.

Search Packages
search_packages(query: str) -> List[Dict]

Search PyPI packages by keywords.

Get Package Releases
get_package_releases(package_name: str) -> Dict

Get all released version information for a specified package.

Get Package Statistics
get_package_stats(package_name: str) -> Dict

Get download statistics for a specified package.

🔧 Configuration

The server uses the MCP protocol to communicate with clients through standard input/output (stdio), no network port configuration needed.

📋 Integration with AI Assistants

Using Claude Desktop

Add the following configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "pypi": {
      "command": "python",
      "args": ["pypi_server.py"]
    }
  }
}
Usage Examples

In your AI assistant, you can call the PyPI MCP tools as follows:

Use PyPI tool to search for Flask package:
@pypi search_packages("flask")

Get detailed information about a specific package:
@pypi get_package_info("requests")

Get information about a specific version of a package:
@pypi get_package_info("django", "4.2.0")

View all released versions of a package:
@pypi get_package_releases("numpy")

Get download statistics for a package:
@pypi get_package_stats("pandas")

📄 License

MIT

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.