Query Package Repositories for LLMs
Pacman MCP Server: AI tool for querying package indices like PyPI, npm, crates.io, Docker Hub, and Terraform Registry. Search and retrieve package info.
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Why it matters
Empower LLMs with the ability to query and retrieve information from diverse package repositories, including PyPI, npm, crates.io, Docker Hub, and Terraform Registry.
Outcomes
What it gets done
Search for packages across multiple repositories.
Retrieve detailed information about specific packages and Docker images.
Query for the latest versions of Terraform modules.
Integrate package querying capabilities into LLM applications.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-pacman | bash Capabilities
Tools your agent gets
Search for packages in package indexes (PyPI, npm, crates.io, Terraform)
Retrieve detailed information about a specific package
Search for Docker images in Docker Hub
Retrieve detailed information about a specific Docker image
Retrieve the latest version of a Terraform module
Overview
Pacman MCP Server
The Pacman MCP Server is a Model Context Protocol (MCP) server that provides AI clients with capabilities to query package indices. It enables searching for packages and retrieving detailed information from repositories such as PyPI, npm, crates.io, Docker Hub, and the Terraform Registry. Use the Pacman MCP Server when an AI agent needs to programmatically search for software packages, Docker images, or Terraform modules across multiple popular registries. It is ideal for integrating package discovery and information retrieval into AI-powered development workflows.
What it does
As an AI agent, my job is to efficiently find and retrieve information about software packages and infrastructure modules to inform development decisions or automate tasks. I need a reliable way to query various package repositories. The Pacman MCP Server allows me to do this by providing tools to search and get details for packages across PyPI, npm, crates.io, Docker Hub, and the Terraform Registry. For example, I can install and run it using:
pip install mcp-server-pacman
Or configure it in an application like Claude.app:
"mcpServers": {
"pacman": {
"command": "python",
"args": ["-m", "mcp_server_pacman"]
}
}
Source README
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 indicesindex(string, required): Package index to search ("pypi", "npm", "crates", "terraform")query(string, required): Package name or search querylimit(integer, optional): Maximum number of results to return (default: 5, max: 50)
package_info- Get detailed information about a specific packageindex(string, required): Package index to query ("pypi", "npm", "crates", "terraform")name(string, required): Package nameversion(string, optional): Specific version to get info for (default: latest)
search_docker_image- Search for Docker images in Docker Hubquery(string, required): Image name or search querylimit(integer, optional): Maximum number of results to return (default: 5, max: 50)
docker_image_info- Get detailed information about a specific Docker imagename(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 modulename(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 nameversion(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 nameversion(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 nameversion(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:
Using uvx
"mcpServers": {
"pacman": {
"command": "uvx",
"args": ["mcp-server-pacman"]
}
}
Using docker
"mcpServers": {
"pacman": {
"command": "docker",
"args": ["run", "-i", "--rm", "oborchers/mcp-server-pacman:latest"]
}
}
Using pip installation
"mcpServers": {
"pacman": {
"command": "python",
"args": ["-m", "mcp-server-pacman"]
}
}
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
mcpkey is needed when using themcp.jsonfile.
Using uvx
{
"mcp": {
"servers": {
"pacman": {
"command": "uvx",
"args": ["mcp-server-pacman"]
}
}
}
}
Using Docker
{
"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 -xvsRun 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_successCheck 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:
- Update the version in
pyproject.toml - Create a new tag with
git tag vX.Y.Z(e.g.,git tag v0.1.0) - Push the tag with
git push --tags
This will automatically:
- Verify the version in
pyproject.tomlmatches the tag - Run tests and lint checks
- Build and publish to PyPI
- Build and publish to Docker Hub as
oborchers/mcp-server-pacman:latestandoborchers/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
FAQ
Common questions
Discussion
Questions & comments · 0
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