{"repo":"2015xli/clangd-graph-rag","free":true,"listed":false,"github":"https://github.com/2015xli/clangd-graph-rag","clone":"git clone https://github.com/2015xli/clangd-graph-rag.git","description":"Source code graph RAG (GraphRAG) for C/C++ development based on clang/clangd","language":"Python","stars":60,"topics":["knowlege-graph","llm-rag","source-code-analysis","clang","clangd","code-graph","rag","graphrag","adk","coding-agents"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"C/C++ Source Code Graph RAG (using Clang/Clangd) This project builds a Neo4j graph RAG (Retrieval-Augmented Generation) for a C/C++ software project based on clang/clangd, which can be queried for deep software project analysis. It works well with large and complex codebases like the Linux, llvm, llama.cpp, etc. The project includes an example MCP server and an AI expert agent. You can also develop your own MCP servers and agents around the graph RAG for your specific purposes, such as: Software Analysis Analyze project organization (folders, files, modules) Analyze code patterns and structures Understand call chains and class relationships Examine architectural design and workflows Trace dependencies and interactions Expert Assistance Code Refactoring Advice : Provide guidance on design improvements and optimizations Bug Analysis : Help identify root causes of bugs or race conditions Documentation : Assist with software design documentation Feature Implementation : Guide on implementing features based on requirements Architecture Review : Analyze and suggest improvements to system architecture --- Current Schema Here is a simplified version of the current neo4j schema for AI agent to use. --- A benchmark: The Linux Kernel When building a code graph for the Linux kernel (WSL2 release) on a workstation (12 cores, 64GB RAM), it takes about 4 hours using 10 parallel worker processes, with peak memory usage at 32GB. Note this process does not include the LLM summary generation, s","default_branch":null,"files":null,"tree":[],"storefront":"/r/2015xli","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/2015xli/clangd-graph-rag/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}