Evaluate AI-generated code against 45 security, cost, and quality judges using built-in AST analysis. For developers integrating code generation into workflows who need automated quality gates.
io.github.KevinRabun/judges
Local install
STDIO
No auth required
How models use it and what it is built for.
Evaluate AI-generated code against 45 security, cost, and quality judges using built-in AST analysis. For developers integrating code generation into workflows who need automated quality gates.
Local install — runs as a subprocess.
Where to find authoritative docs and source for Judges Panel.
Paste any of these into Agent Studio after connecting Judges Panel.
Common questions about connecting and running Judges Panel.
What do the 45 judges evaluate?
The judges assess AI-generated code across three dimensions: security vulnerabilities, cost/efficiency, and code quality. They use abstract syntax tree (AST) analysis to perform deep code inspection beyond simple pattern matching.
What languages does this server support?
The registry metadata does not specify supported languages. Check the documentation or run `npx @kevinrabun/judges@3.129.9 --help` to see which languages the AST-based judges can analyze.
How do I install and use this MCP server?
Install via `npx @kevinrabun/judges@3.129.9`. The server uses stdio transport, so connect it to your MCP client and pass code snippets to evaluate against the judge rules.
Can I customize which judges run on my code?
The registry metadata does not specify customization options. Refer to the project documentation to learn whether you can enable/disable specific judges or create custom evaluation rules.
Is this suitable for CI/CD pipelines?
Yes—the stdio transport and automated evaluation of 45 judges make it suitable for integrating code quality gates into CI/CD workflows. Exact integration steps depend on your pipeline tool; consult the project docs for examples.
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