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Code Review Graph
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on…
Install
pip install code-review-graphInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →code-review-graph
A local code knowledge graph that gives AI coding tools precise review context over MCP.
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Usage · Commands · FAQ · Troubleshooting · GitHub Action · Reproducing the benchmarks · Roadmap
AI coding tools often re-read large parts of a codebase to review a change. code-review-graph builds a structural map of the code with Tree-sitter, keeps it updated incrementally, and serves compact context over MCP, so the assistant reads only the files a change touches.
Quick Start
pip install code-review-graph # or: pipx install code-review-graph
code-review-graph install # detect installed AI coding tools and configure each one
code-review-graph build # parse the codebase
install detects which AI coding tools you have, writes an MCP server entry for each, installs hooks and skills where the platform supports them, and adds graph instructions to the platform's rules file. The MCP entry uses poetry run or uv run inside a Poetry or uv project environment, uvx code-review-graph serve when uvx is on PATH, and otherwise the current Python interpreter. Restart the editor or tool afterwards.
To configure one platform, pass --platform with one of codex, claude-code, cursor, windsurf, zed, continue, opencode, antigravity, gemini-cli, qwen, kiro, qoder, copilot, copilot-cli, codebuddy, or hermes:
code-review-graph install --platform cursor
code-review-graph install --platform codebuddy
Config file locations are listed in docs/USAGE.md. Requires Python 3.10+.
uninstall removes CRG-owned files and entries from a Git or SVN working tree and leaves other MCP servers, hooks, skills and JSONC comments alone. Run it from anywhere inside the tree. Shared config files are replaced atomically, so a failed write leaves the original intact.
code-review-graph uninstall --dry-run # preview only
code-review-graph uninstall # preview, confirm, apply
code-review-graph uninstall --yes # apply without prompting
code-review-graph uninstall --all-repos # also clean every registered repository
code-review-graph uninstall --keep-data # remove integrations, keep graph databases
code-review-graph uninstall --keep-user-configs --repo . # this project only
Then open the project and ask the assistant:
Build the code review graph for this project
Build time scales with repository size; a cold build of a ~3,000-file repository took about 40 seconds (measured). After that, hooks and watch mode keep the graph updated. If some files fail to parse, the result has status partial and names them in its summary; the CLI also prints a Warning: line on stderr, and those files keep their previous graph rows.
How It Works
The repository is parsed into ASTs with Tree-sitter and stored as a graph of nodes (functions, classes, imports) and edges (calls, inheritance, test coverage). At review time the graph is queried for the smallest set of files the assistant needs to read.
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