code-review-graph: Local-first code intelligence graph for MCP and CLI

by tirth8205 · MCP Server · ★ 32.6k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: Code Review

How to install code-review-graph

pip install code-review-graph
pip install code-review-graph[embeddings]          # Local vector embeddings (sentence-transformers)

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-codingclaudeclaude-codecode-reviewgraphragincrementalknowledge-graphllmmcppython

Quick Facts

Stars32,627
Forks2,967
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score69/100
Open Issues113
Last Updated2026-11-06
Created2026-02-26
Platformsclaude-code, cli, mcp, python
Est. Tokens~16k

About code-review-graph

code-review-graph Stop burning tokens. Start reviewing smarter. Claude Code re-reads your entire codebase on every task. fixes that. It builds a structural map of your code with Tree-sitter, tracks changes incrementally, and gives Claude precise context so it reads only what matters. <img src="diagrams/diagram1beforevsafter.png" alt="The Token Problem: 6.8x fewer tokens with higher r

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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