code-review-graph vs Graft
Side-by-side comparison of two AI agent tools
Short answer
- Graft is growing faster: +870 GitHub stars in the last 30 days vs +220 for code-review-graph.
- Pick code-review-graph for: local code knowledge graph serving compact review context to AI coding tools over MCP. Pick Graft for: turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual.
From GitHub data refreshed daily.
c
code-review-graphopen-source
Local code knowledge graph serving compact review context to AI coding tools over MCP
G
Graftopen-source
Turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual understanding specific to your codebase.
Metrics
| code-review-graph | Graft | |
|---|---|---|
| Stars | 31.9k | 9.5k |
| Star velocity /mo | 220 | 870 |
| Commits (90d) | 665 | 506 |
| Releases (6m) | 10 | 0 |
| Downloads (30d, npm + PyPI) | 297.0K | — |
| Overall score | 0.7208179595910345 | 0.7068809558403568 |
FAQ
- Which is more popular, code-review-graph or Graft?
- code-review-graph has more GitHub stars (31,898 vs 9,520).
- Which is more actively developed, code-review-graph or Graft?
- code-review-graph had more commits in the last 90 days (665 vs 506).
- Should I use code-review-graph or Graft?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.