vinv.ai/open source · Apache 2.0

mcp server · python · 100% local

The MCP server that gives your coding agent runtime evidence

Vinv is an MCP server for Python: point Claude Code, Cursor, Copilot, Codex or any MCP client at your repo and it serves semantic code search, runtime traces, fault localization, dead-code detection and a verify/optimize loop — everything runs locally, no API keys.

Install → pip install vinv · claude mcp add --scope user vinv -- npx -y vinv-mcp · 100% local, Apache 2.0.

Install the engines, then register the server. It discovers your open workspace automatically via MCP roots, so one global config follows whatever repo you have open.

pip install vinvclaude mcp add --scope user vinv -- npx -y vinv-mcpcodex mcp add vinv -- npx -y vinv-mcpgemini mcp add --scope user vinv npx -- -y vinv-mcp

For any other client, add { "command": "npx", "args": ["-y", "vinv-mcp"] } under mcpServers.vinv. See vinv-mcp on npm.

One server, the full tool set:

  • vinv_query — semantic code search: ask by meaning, get ranked symbols with bodies and line numbers.
  • vinv_deadcode — code nothing references, from static analysis; works with no index or runtime.
  • vinv_index — build/refresh the semantic index (in the background).
  • rank_suspects — fault localization over real pass/fail runs, error messages attached.
  • values_of · slice · coverage_of · callers_of · blast_radius · why_did_this_run — live runtime evidence per call, joined to source.
  • vinv_session — drive the verify/optimize loop and read what Vinv observed, from chat.

Most MCP servers hand your agent more static context. Vinv hands it runtime evidence — real traces, argument values and the failing frame — and then re-runs the code to verify a fix actually works. The agent argues from what the code did, not from what it guessed.