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[GitHub Trending] colbymchenry/codegraph

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A pre-indexed code graph reducing token usage for AI coding tools; novel and highly actionable for developers.

2026-05-19 AI/ML github.com
Pre-indexed code knowledge graph for Claude Code, Codex, Cursor, and OpenCode — fewer tokens, fewer tool calls, 100% local - colbymchenry/codegraph
Summary

CodeGraph pre-indexes codebases into knowledge graphs of symbol relationships and call graphs, enabling AI agents to answer complex queries with 92% fewer tool calls and 71% faster exploration, as benchmarked across six codebases including VS Code and Swift Compiler (25,874 files, 272,898 nodes indexed in <4 minutes, zero file reads). Compatible with Claude Code, Cursor, Codex CLI, and OpenCode, it runs locally, handles cross-language queries (Python+Rust, Swift/C++), and includes features like full-text search (FTS5) and impact analysis, with the Java codebase requiring just one codegraph_explore call to answer a full question.

Key Takeaways
  • Integrate CodeGraph into your AI coding agent stack to slash token consumption and exploration latency by an order of magnitude without sacrificing accuracy.
Why it matters

For a solutions architect optimizing AI-assisted development pipelines, CodeGraph directly attacks the token and latency overhead of agentic code exploration by replacing expensive file scanning with instant graph lookups.

Author

colbymchenry