codeweave-mcp

Name: codeweave-mcp
Author: semihkayan

semihkayan March 28, 2026

3 copies 0 downloads

MCP server that gives AI agents deep code understanding. Builds AST, call graphs, type graphs, and hybrid semantic search — so your agent queries structured indexes instead of dumping files into context. 7 languages. Zero config. One command setup.

<p align="center"> <h1 align="center">@codeweave/mcp</h1> <p align="center"> <strong>Give your AI agent structured code understanding — not just file dumps.</strong> </p> <p align="center"> <a href="https://www.npmjs.com/package/@codeweave/mcp"><img src="https://img.shields.io/npm/v/@codeweave/mcp.svg" alt="npm version"></a> <a href="https://github.com/semihkayan/codeweave-mcp/blob/main/LICENSE"><img src="https://img.shields.io/npm/l/@codeweave/mcp.svg" alt="license"></a> <img src="https://img.shields.io/badge/node-%3E%3D20-brightgreen" alt="node version"> <img src="https://img.shields.io/badge/languages-7-blue" alt="supported languages"> <img src="https://img.shields.io/badge/status-active%20development-orange" alt="status"> </p> </p>

CodeWeave is an MCP server that gives AI agents cheap, precise code intelligence. Instead of dumping entire files into context, your agent queries local indexes — AST, call graph, type graph, hybrid semantic search — and gets back only what it needs.

Less tokens. More relevant context. Better decisions.

The semantic search pipeline is the heart of the system: a 6-stage hybrid engine combining vector embeddings, full-text search, and structural density scoring. Tested extensively across large production codebases — Java monoliths, TypeScript monorepos, Python ML pipelines, Go microservices — with consistently strong retrieval accuracy.

Actively developed. New tools and improvements ship regularly. Contributions and feedback are welcome.

Quick Start

cd your-project
npx @codeweave/mcp

That's it. The setup wizard handles everything:

Installs @codeweave/mcp globally
Installs Ollama if needed
Downloads the embedding model
Configures your MCP client (Claude Code, VS Code)
Indexes your project

Note: The first run requires a one-time download of Ollama and the embedding model. This takes a few minutes but only happens once.

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