code-review-graph vs mcp-use
Side-by-side comparison of two AI agent tools
Short answer
- code-review-graph is growing faster: +330 GitHub stars in the last 30 days vs +195 for mcp-use.
- Pick code-review-graph for: local code knowledge graph serving compact review context to AI coding tools over MCP. Pick mcp-use for: the fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
From GitHub data refreshed daily.
c
code-review-graphopen-source
Local code knowledge graph serving compact review context to AI coding tools over MCP
m
mcp-useopen-source
The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
Metrics
| code-review-graph | mcp-use | |
|---|---|---|
| Stars | 31.9k | 10.7k |
| Star velocity /mo | 330 | 195 |
| Commits (90d) | 665 | 665 |
| Releases (6m) | 10 | 10 |
| Overall score | 0.7583554607364194 | 0.7614806982370892 |
FAQ
- Which is more popular, code-review-graph or mcp-use?
- code-review-graph has more GitHub stars (31,898 vs 10,717).
- Which is more actively developed, code-review-graph or mcp-use?
- code-review-graph had more commits in the last 90 days (665 vs 665).
- Should I use code-review-graph or mcp-use?
- 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.