About

In AI-assisted code review, token consumption and context window limits have always been the core bottlenecks holding back efficiency. code-review-graph was built to solve exactly that problem. It is a persistent code knowledge graph tool designed on local-first principles, offering both MCP (Model Context Protocol) and CLI support to deliver efficient, precise local code intelligence for AI code review. By building and maintaining a resident local code relationship graph, the tool compresses average context data to under 8.2x its original size, dramatically cutting token overhead while improving the depth and accuracy of code reviews.

Key Features

Persistent local code graph: Automatically scans and indexes project code structure, building a call-and-dependency graph across functions, classes, and files, all stored locally.

30 MCP tools: Provides 30 dedicated MCP tools covering code search, symbol lookup, dependency analysis, and change impact assessment, seamlessly integrating with any MCP-compatible AI client.

Smart context compression: When an AI review request comes in, only the code snippets and dependency relationships directly tied to the current change are extracted, achieving an average 8.2x reduction in context size.

CLI support: A full command-line interface lets developers query and analyze the graph directly from CI/CD pipelines or a local terminal.

Pricing & Fees

Pricing: Not publicly listed on the pages we reviewed; check the official site for current plans.
License: The project is open source under the MIT license, and the source code is available on GitHub.
Local-first storage: All code indexes and graph data (`.code-review-graph/graph.db`) stay on your local machine, with nothing uploaded to third-party servers.
Token cost savings: Precision context pruning reduces tokens per AI request — the project reports 8.2x average context reduction in its review benchmark and up to 49x in documented large-repo workflows.
Platform availability: Works via MCP and CLI with AI coding tools including Claude Code, Codex, Cursor, Windsurf, Zed, VS Code-based setups, GitHub Copilot, and Gemini CLI.

Who It's For

This tool is built for heavy AI-assisted development users who frequently rely on AI for code review, refactoring suggestions, or bug detection and want to cut API costs while improving feedback quality. It also serves large project maintenance teams working with hundreds of thousands or even millions of lines of code who need to quickly assess change impact, as well as DevOps and CI/CD engineers looking to embed intelligent review steps into automated pipelines with zero manual intervention via CLI. Finally, it is ideal for security-conscious teams that cannot send code to cloud AI services due to compliance or security policies but still want the benefits of AI-assisted code review.

About

Key Features

Pricing & Fees

Who It's For

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