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code-review-graph

tirth8205/code-review-graph

Local-first code intelligence graph for MCP and CLI.

GraphCanon updated today · GitHub synced today · 27 views this month

31k stars2.8k forksLast push 3d Python MIT

Decision brief

code-review-graph provides a local-first code intelligence graph specifically for MCP and CLI, optimizing AI coding tool reviews by focusing on necessary contexts in large repositories.

Good fit when

  • When working with extensive codebases where context-specific reviews are essential
  • If you use AI coding tools that require optimized, contextual data to enhance their performance

Avoid when

  • For projects that do not benefit from a persistent map of codebase contexts, like small independent scripts
  • If developers prefer cloud-based continuous integration setups over local-first solutions for code intelligence enhancement

Observed Jul 16, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Very active (3d since push)
As of today
Provenance
Not a fork · Personal account
As of today
Security (OSV)
No MCP manifest
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install code-review-graph
PyPI

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A persistent map of your codebase optimized for AI coding tools to ensure efficient and contextually relevant reviews, especially in large repositories through benchmarked reductions.

Capability facts

CLI
CLI entrypoint

Source: pyproject.toml:[project.scripts] · Aug 26, 2026

Languages
python

Source: github.language+pyproject.toml · Aug 26, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 26, 2026)

Requires Python 3.10+. For the best experience, install [uv](https://docs.astral.sh/uv/) (the MCP co
Source link
Works with CursorCursor

Source: README excerpt (regex_v1, Aug 26, 2026)

="One Install, Every Platform: auto-detects Codex, Claude Code, CodeBuddy Code, Cursor, Windsurf, Zed, Continue, OpenCode, Antigravity, Gemini CLI, Qwen, Qoder, Kiro,
Source link
Works with VS CodeVS Code

Source: README excerpt (regex_v1, Aug 26, 2026)

e-review-graph install --platform copilot # configure only GitHub Copilot (VS Code)
Source link

Tags

README

Quick Start

pip install code-review-graph                     # or: pipx install code-review-graph
code-review-graph install          # auto-detects and configures all supported platforms
code-review-graph build            # parse your codebase

One command sets up everything. install detects which AI coding tools you have, writes the correct MCP configuration for each one, installs platform-native hooks/skills where supported, and injects graph-aware instructions into your platform rules. It auto-detects whether you installed via uvx or pip/pipx and generates the right config. Restart your editor/tool after installing.

To target a specific platform:

code-review-graph install --platform codex       # configure only Codex
code-review-graph install --platform cursor      # configure only Cursor
code-review-graph install --platform claude-code  # configure only Claude Code
code-review-graph install --platform gemini-cli   # configure only Gemini CLI
code-review-graph install --platform antigravity   # configure only Antigravity
code-review-graph install --platform windsurf     # configure only Windsurf
code-review-graph install --platform zed          # configure only Zed
code-review-graph install --platform continue     # configure only Continue
code-review-graph install --platform opencode     # configure only OpenCode
code-review-graph install --platform qwen         # configure only Qwen
code-review-graph install --platform qoder        # configure only Qoder
code-review-graph install --platform kiro         # configure only Kiro
code-review-graph install --platform copilot      # configure only GitHub Copilot (VS Code)
code-review-graph install --platform copilot-cli  # configure only GitHub Copilot CLI
code-review-graph install --platform codebuddy    # configure only CodeBuddy Code
code-review-graph install --platform hermes       # configure only Hermes Agent

Requires Python 3.10+. For the best experience, install uv (the MCP config will use uvx if available, otherwise falls back to the code-review-graph command directly).

To remove CRG from a Git or SVN project, use the symmetric uninstall command from anywhere inside its working tree. The target is normalized to the working tree root, and non-repository directories are refused. It removes only CRG-owned files and entries; unrelated MCP servers, hooks, skills, and JSONC comments remain untouched. Shared configuration changes use atomic replacement so a failed write leaves the original file intact.

code-review-graph uninstall --dry-run    # preview every action; write nothing
code-review-graph uninstall              # preview, ask for confirmation, then 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 but keep graph databases
code-review-graph uninstall --keep-user-configs --repo .  # clean this project only

Then open your project and ask your AI assistant:

Build the code review graph for this project

The initial build takes ~10 seconds for a 500-file project. After that, watch mode and supported hooks can keep the graph updated automatically.

For agents

This page has a .md twin and JSON over the API.

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