codebase-memory-mcp

The fastest and most efficient code intelligence engine for AI coding agents. Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a native executable with a small verified runtime-asset set for macOS, Linux, and Windows — download, run `install`, done.

High-quality parsing through tree-sitter AST analysis across all 162 languages, enhanced with Hybrid LSP semantic type resolution for Python, TypeScript / JavaScript / JSX / TSX, PHP, C#, Go, C, C++, Java, Kotlin, Rust, and Perl — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 17 MCP tools. No language runtime, hosted service, or API key. Plug and play across 45 supported automatic/conditional client surfaces.

Research — The design and benchmarks behind this project are described in the preprint Codebase-Memory: Tree-Sitter-Based Knowledge Graphs for LLM Code Exploration via MCP (arXiv:2603.27277). Evaluated across 31 real-world repositories: 83% answer quality, 10× fewer tokens, 2.1× fewer tool calls vs. file-by-file exploration.

Security & Trust — This tool reads your codebase and writes to your agent configuration files. That is what it is designed to do. If you prefer to audit before running, the full source is here. For each release product, three behaviourally identical executable candidates (unstripped, debug-stripped, stripped) are submitted to VirusTotal before testing; the selected candidate is then packaged with its SHA-256 unchanged. Release notes link every measured candidate result. Publication permits on…