code-review-graph
About
code-review-graph is an AI-assisted code review tool that builds a structural map of code using Tree-sitter and incrementally tracks changes to provide precise context to AI assistants via the Model Context Protocol (MCP). This approach significantly reduces token consumption by enabling AI models to read only the minimal set of files relevant to a change, rather than the entire codebase. It aims to solve the token waste problem in large repositories and monorepos, improving the efficiency and quality of AI code reviews.
Features
- Code Graph-based Token Optimization and Reduction
- Incremental Code Change Analysis and Updates
- Broad Multi-language Support (23+ languages & Jupyter Notebooks)
- Precise Context Provision for AI Assistants (MCP Compatible)
- Blast-Radius Impact Analysis of Changes
Supported Platforms
Links
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