UV MCP

What I Do

Describe how to steer the uv-mcp server so natural language requests become precise uv workflows. This skill focuses on diagnosing environments, managing dependencies, controlling Python runtimes, and building artifacts with uv while keeping the workspace healthy.

Core Workflows

Environment Health & Setup

Intent	Tool	What Happens
Diagnose failures or missing environments	`diagnose_environment`	Confirms `pyproject.toml`, virtualenv presence, lock sync status, and reports remediation steps.
Repair broken setups	`repair_environment`	Creates `.venv`, installs Python, and syncs dependencies automatically.
Verify/install uv itself	`check_uv_installation`, `install_uv`	Checks uv availability and returns platform-specific install steps when missing.