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CodeGraph RAG

CodeGraph RAG turns your monorepo into a queryable knowledge graph — ask questions, understand architecture, and edit multi-language codebases with AI.

★ 4,655 GitHub MIT ragmcpknowledge-graphmonorepolocal-firstcode-intelligence RAG & Knowledge

Overview

CodeGraph RAG is a local-first code intelligence platform that indexes your entire monorepo into a hybrid knowledge graph combining Memgraph (graph database) and Qdrant (vector database). It lets developers query codebases in natural language, explore cross-language dependencies, understand architecture, and even perform AI-assisted edits across dozens of languages using tree-sitter parsing. It ships as both a CLI and an MCP (Model Context Protocol) server, so it plugs directly into Cursor, Claude Code, and other AI assistants. Self-hosted, MIT-licensed, and designed for monorepos of any size.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Affiliate disclosure

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  code-graph-rag:
    image: ghcr.io/vitali87/code-graph-rag:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/code-graph-rag:/data

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Guides & articles

CodeGraph RAG Tutorial: Query and Edit Your Codebase with MCP + AI

Step-by-step tutorial: index a repository with CodeGraph RAG, query it in natural language, and connect it to Claude Code or Cursor via MCP for AI-assisted edits.

Aug 19, 2026

CodeGraph RAG: Turn Your Monorepo into a Queryable Knowledge Graph

CodeGraph RAG combines Memgraph and Qdrant into a hybrid knowledge graph for local-first code intelligence. Learn how it answers natural-language questions about your monorepo across 14+ languages.

Aug 19, 2026