
astral uv mcp
uv-mcp is an MCP server that wraps Astral's ultra-fast uv Python package manager, enabling AI agents to diagnose, repair, and manage Python environments through natural language.
Overview
astral uv mcp (commonly known as uv-mcp) is an open-source Model Context Protocol (MCP) server that bridges Astral's uv—the extremely fast Rust-based Python package and project manager—with AI agents and tools like Claude Desktop, Claude Code, and Gemini CLI.
Instead of AI assistants merely suggesting uv commands, uv-mcp allows them to directly inspect, diagnose, and fix Python project environments, making AI a proactive DevOps partner for Python development.
Features
- Environment Diagnostics: Automatically analyzes project structure, virtual environments, dependency conflicts, lockfiles (
uv.lock), andpyproject.toml. - Self-Healing Repairs: Creates virtual environments, initializes projects, syncs dependencies, and resolves issues with a single tool call.
- Dependency Management: Add, remove, or update packages (including dev dependencies) via natural language—no need to remember flags or commands.
- Native uv Integration: Fully respects
uvworkflows, PEP 668 externally-managed environments, and ensures reproducible setups withuv.lock. - MCP Compatibility: Works seamlessly with MCP clients including Claude, Gemini CLI extensions, and other AI agent platforms.
- Scoped & Safe: Operations are project-scoped with no global pollution; ideal for containers, CI/CD, and managed environments.
- Auditable & Deterministic: Clear logs and consistent behavior across machines for reliable automation.
Use Cases
- AI-Powered Python Setup: Tell your agent "Set up a new data science project with pandas and Jupyter"—it handles
uv init, venv creation, and dependency installation. - Environment Troubleshooting: AI diagnoses "why my project isn't running" and repairs it automatically.
- Dependency Resolution: Resolve conflicts or update lockfiles without manual intervention.
- Multi-Agent Workflows: Integrate into larger MCP/AI agent orchestrations for full-stack Python development automation.
- CI/CD & Reproducible Builds: Ensure consistent environments in automated pipelines.
Installation & Quick Start
For Gemini CLI (recommended)
gemini extensions install https://github.com/saadmanrafat/uv-mcp
For Claude Desktop / Code
Clone the repo and add to your MCP configuration (details in the documentation).
Requires uv (Astral's package manager) to be installed. Full guides available in the repository.
Why uv-mcp?
uv is already 10-100x faster than traditional tools like pip/Poetry. uv-mcp supercharges it by giving AI agents direct, safe access to its power—turning "it works on my machine" into reliable, agent-driven reproducibility.
Links
- GitHub: saadmanrafat/uv-mcp
- Documentation: saadman.dev/uv-mcp
- uv Official Docs: docs.astral.sh/uv
Built for the modern AI-native Python ecosystem.