About uv-mcp
uv-mcp is an MCP server for inspecting and managing Python environments through uv. It is intended for LLM-assisted dependency work and troubleshooting, exposing environment data alongside package-management tools.
Key features
- 01Inspect installed and outdated packages
- 02Check package compatibility
- 03Compare package sets across environments
- 04Parse and validate requirements files
- 05Manage virtual environments and dependencies
Use cases
- 01Review packages and versions in an environment
- 02Check whether dependencies are compatible
- 03Compare local and production environments
MCP support
The MCP server exposes Python package and requirements-file resources, along with tools for uv, pip, and environment management.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEuv-mcp
A Model Context Protocol (MCP) server for interacting with Python installations via uv, the fast Python package installer.
Overview
uv-mcp provides LLMs with direct access to inspect and manage Python environments through the uv package manager. This allows AI assistants to help with Python dependency management, environment inspection, and troubleshooting tasks.
Features
- Environment Inspection: Query installed packages and their versions
- Dependency Resolution: Check compatibility between packages
- Environment Comparison: Identify differences between local and cloud/production environments
- Requirement Management: Parse and validate requirements files
- Package Information: Retrieve metadata about PyPI packages
- Virtual Environment Management: Create and manage virtual environments
How It Works
uv-mcp implements the Model Context Protocol to expose Python environment data and package management functionality through standardized resources and tools.
Resources
python:packages://installed- List of all installed packages and versionspython:packages://outdated- List of installed packages with newer versions availablepython:packages://{package_name}/latest- Latest versions available for a packagepython:packages://{package_name}/dependencies- List of dependencies for a specific packagepython:requirements://{file_path}- Parsed content of requirements files
Tools
run(command: str[])- Run a command or scriptinit()- Create a new projectadd(package_name: str, version: Optional[str])- Add dependencies to the projectremove(package_name: str)- Remove dependencies from the projectsync(dry_run: bool)- Install all declared dependencies, uninstall anything not declaredlock()- Update the project's lockfilepip(command: str[])- Run a pip commandpip_install(package_name: str, version: Optional[str])- Install a package using pippip_uninstall(package_name: str)- Uninstall a package using pippip_list()- List all installed packages using pip
Usage
To start the server:
uvx uv-mcp
Development
This project is built with the MCP Python SDK and uv.
Comments
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.