DeusData/codebase-memory-mcp: README-based editorial guide

DeusData/codebase-memory-mcp describes itself in the README as "High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph , average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.". This article keeps to facts that can be checked in the repository. Stars, forks, and promotional badges are signals of attention, not proof of quality. Under "codebase-memory-mcp", the README says: 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.. That establishes the project's stated boundary, not a production test.

The README's "Why codebase-memory-mcp" section gives a useful starting point for deciding whether the project fits: Plug and play , single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys. Download → install → restart agent → done.. If that problem is not yours, popularity is a poor reason to adopt it. Project names, commands, and component names are kept as written so a reader can return to the primary source without guessing at terminology. Another checkable README item is: Extreme indexing speed , Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline: LZ4 compression, in-memory SQLite, fused Aho-Corasick pattern matching. Memory released after indexing.. It can shape a first test, but it does not replace testing in the intended environment.

The operating model is spread across sections such as "codebase-memory-mcp". The source evidence includes: > 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.. This article does not turn missing architecture, performance, or security details into claims. A real deployment still needs a look at the repository layout, configuration files, and release history.