07-22
Local-first code intelligence graph for AI coding tools
code-review-graph is a local-first code intelligence graph that parses codebases with Tree-sitter and provides precise context to AI coding tools via the MCP protocol. It solves the problem of AI assistants re-reading large amounts of tokens during code review by performing blast-radius analysis to output only affected files. Features include 30+ MCP tools, incremental updates (<2s), a risk-scored GitHub Action for PR reviews, and support for custom languages. Benchmarks show median token reduction of 82x. Ideal for developers using AI coding assistants and teams maintaining large monorepos.