@GitHub_Daily: When using AI-assisted programming, asking a simple question requires flipping through files one by one, which wastes tokens and easily leads to wrong context. codebase-memory-mcp parses the entire codebase into a knowledge graph, allowing AI to directly 'understand' the project structure. A single executable written in pure C, zero dependencies, …

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codebase-memory-mcp is a tool written in pure C that parses the entire codebase into a knowledge graph, supports 158 programming languages, is compatible with 11 AI coding agent tools, greatly improving AI's understanding of project structure and reducing token consumption.

When using AI-assisted programming, asking a simple question requires flipping through files one by one, which wastes tokens and easily leads to wrong context. codebase-memory-mcp parses the entire codebase into a knowledge graph, allowing AI to directly 'understand' the project structure. A single executable written in pure C, zero dependencies. Download and set it up with one command. Indexing speed is impressive: 28 million lines of Linux kernel code processed in 3 minutes. GitHub: http://github.com/DeusData/codebase-memory-mcp… Supports syntax parsing for 158 programming languages, can trace function call chains across files, identify interface routes, and detect dead code. Compatible with 11 agent coding tools including Claude Code, Gemini CLI, Codex, and comes with a 3D graph visualization. If you often use AI to write code and feel it lacks understanding of the overall project, this tool is worth a try.
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Built-in 3D graph visualization (UI variant) — explore your knowledge graph at localhost:9749

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