What is Mcp Server Pacman

mcp-server-pacman is a Model Context Protocol server that provides capabilities for querying package indices. It allows Large Language Models (LLMs) to search and retrieve information from various package repositories such as PyPI, npm, crates.io, Docker Hub, and Terraform Registry.

Use cases

Use cases for mcp-server-pacman include automating the retrieval of package information for software projects, enhancing development tools with package search capabilities, integrating with CI/CD systems to ensure the latest dependencies are used, and providing developers with quick access to Docker images and Terraform modules.

How to use

To use mcp-server-pacman, you can utilize its available tools like search_package to find packages, package_info to get detailed information about a specific package, search_docker_image for Docker images, and terraform_module_latest_version to fetch the latest version of a Terraform module. Each tool requires specific parameters to execute queries effectively.

Key features

Key features of mcp-server-pacman include the ability to search across multiple package indices, retrieve detailed package information, search for Docker images, and access the latest versions of Terraform modules. It supports multiple programming languages and platforms.

Where to use

mcp-server-pacman can be used in software development environments, particularly in scenarios involving package management, dependency resolution, and continuous integration/continuous deployment (CI/CD) pipelines. It is beneficial for developers working with Python, JavaScript, Rust, Docker, and Terraform.

Pacman MCP Server

A Model Context Protocol server that provides package index querying capabilities. This server enables LLMs to search and retrieve information from package repositories like PyPI, npm, crates.io, Docker Hub, and Terraform Registry.

Available Tools

• search_package - Search for packages in package indices

  • index (string, required): Package index to search (“pypi”, “npm”, “crates”, “terraform”)
  • query (string, required): Package name or search query
  • limit (integer, optional): Maximum number of results to return (default: 5, max: 50)

• package_info - Get detailed information about a specific package

  • index (string, required): Package index to query (“pypi”, “npm”, “crates”, “terraform”)
  • name (string, required): Package name
  • version (string, optional): Specific version to get info for (default: latest)

• search_docker_image - Search for Docker images in Docker Hub

  • query (string, required): Image name or search query
  • limit (integer, optional): Maximum number of results to return (default: 5, max: 50)

• docker_image_info - Get detailed information about a specific Docker image

  • name (string, required): Image name (e.g., user/repo or library/repo)
  • tag (string, optional): Specific image tag (default: latest)

• terraform_module_latest_version - Get the latest version of a Terraform module

  • name (string, required): Module name (format: namespace/name/provider)

Prompts

• search_pypi

  • Search for Python packages on PyPI
  • Arguments:
    • query (string, required): Package name or search query

• pypi_info

  • Get information about a specific Python package
  • Arguments:
    • name (string, required): Package name
    • version (string, optional): Specific version

• search_npm

  • Search for JavaScript packages on npm
  • Arguments:
    • query (string, required): Package name or search query

• npm_info

  • Get information about a specific JavaScript package
  • Arguments:
    • name (string, required): Package name
    • version (string, optional): Specific version

• search_crates

  • Search for Rust packages on crates.io
  • Arguments:
    • query (string, required): Package name or search query

• crates_info

  • Get information about a specific Rust package
  • Arguments:
    • name (string, required): Package name
    • version (string, optional): Specific version

• search_docker

  • Search for Docker images on Docker Hub
  • Arguments:
    • query (string, required): Image name or search query

• docker_info

  • Get information about a specific Docker image
  • Arguments:
    • name (string, required): Image name (e.g., user/repo)
    • tag (string, optional): Specific tag

• search_terraform

  • Search for Terraform modules in the Terraform Registry
  • Arguments:
    • query (string, required): Module name or search query

• terraform_info

  • Get information about a specific Terraform module
  • Arguments:
    • name (string, required): Module name (format: namespace/name/provider)

• terraform_latest_version

  • Get the latest version of a specific Terraform module
  • Arguments:
    • name (string, required): Module name (format: namespace/name/provider)

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will
use uvx to directly run mcp-server-pacman.

Using PIP

Alternatively you can install mcp-server-pacman via pip:

pip install mcp-server-pacman

After installation, you can run it as a script using:

python -m mcp_server_pacman

Using Docker

You can also use the Docker image:

docker pull oborchers/mcp-server-pacman:latest
docker run -i --rm oborchers/mcp-server-pacman

Configuration

Configure for Claude.app

Add to your Claude settings:

Configure for VS Code

For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

Note that the mcp key is needed when using the mcp.json file.

{
  "mcp": {
    "servers": {
      "pacman": {
        "command": "uvx",
        "args": [
          "mcp-server-pacman"
        ]
      }
    }
  }
}

{
  "mcp": {
    "servers": {
      "pacman": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "oborchers/mcp-server-pacman:latest"
        ]
      }
    }
  }
}

Customization - User-agent

By default, the server will use the user-agent:

ModelContextProtocol/1.0 Pacman (+https://github.com/modelcontextprotocol/servers)

This can be customized by adding the argument --user-agent=YourUserAgent to the args list in the configuration.

Development

Running Tests

• Run all tests:

  uv run pytest -xvs
  

• Run specific test categories:

  # Run all provider tests
  uv run pytest -xvs tests/providers/
  
  # Run integration tests for a specific provider
  uv run pytest -xvs tests/integration/test_pypi_integration.py
  
  # Run specific test class
  uv run pytest -xvs tests/providers/test_npm.py::TestNPMFunctions
  
  # Run a specific test method
  uv run pytest -xvs tests/providers/test_pypi.py::TestPyPIFunctions::test_search_pypi_success
  

• Check code style:

  uv run ruff check .
  uv run ruff format --check .
  

• Format code:

  uv run ruff format .
  

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-server-pacman

Or if you’ve installed the package in a specific directory or are developing on it:

cd path/to/pacman
npx @modelcontextprotocol/inspector uv run mcp-server-pacman

Release Process

The project uses GitHub Actions for automated releases:

1. Update the version in pyproject.toml
2. Create a new tag with git tag vX.Y.Z (e.g., git tag v0.1.0)
3. Push the tag with git push --tags

This will automatically:

• Verify the version in pyproject.toml matches the tag
• Run tests and lint checks
• Build and publish to PyPI
• Build and publish to Docker Hub as oborchers/mcp-server-pacman:latest and oborchers/mcp-server-pacman:X.Y.Z

Project Structure

The codebase is organized into the following structure:

src/mcp_server_pacman/
├── models/             # Data models/schemas
├── providers/          # Package registry API clients
│   ├── pypi.py         # PyPI API functions
│   ├── npm.py          # npm API functions
│   ├── crates.py       # crates.io API functions
│   ├── dockerhub.py    # Docker Hub API functions
│   └── terraform.py    # Terraform Registry API functions
├── utils/              # Utilities and helpers
│   ├── cache.py        # Caching functionality
│   ├── constants.py    # Shared constants
│   └── parsers.py      # HTML parsing utilities
├── __init__.py         # Package initialization
├── __main__.py         # Entry point
└── server.py           # MCP server implementation

Tests follow a similar structure:

tests/
├── integration/        # Integration tests (real API calls)
├── models/             # Model validation tests
├── providers/          # Provider function tests
└── utils/              # Test utilities

Contributing

We encourage contributions to help expand and improve mcp-server-pacman. Whether you want to add new package indices, enhance existing functionality, or improve documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see:
https://github.com/modelcontextprotocol/servers

Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-server-pacman even more powerful and useful.

License

mcp-server-pacman is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.