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Validate AI-generated code against real codebases before bugs reach runtime.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CodeGuardian MCP" yet — see the docs or source repo.
Use CodeGuardian MCP to validate this AI-generated code against my repository, identify missing functions, incorrect API calls, and dead code, then suggest fixes.
A list of codebase mismatches, risk notes, and actionable fixes.
Use CodeGuardian MCP to review this AI-generated patch, confirm it references real modules, methods, and configs, and flag anything likely to fail at runtime.
Validation results for patch references, with high-risk changes and likely runtime errors flagged.
I used AI to refactor part of the code. Use CodeGuardian MCP to check whether API signatures, dependency calls, and import paths remain compatible with the current codebase.
An API compatibility report listing broken calls, incorrect import paths, and code locations that need coordinated updates.
Verify AI-generated code for quality, security, and performance with more trust.
Scan AI-generated code for injections, secrets, SSRF, and risky patterns.
Validate AI-generated code with browser tests, evidence capture, and smart diagnostics.
Analyze TypeScript and Prisma codebases to prevent risky changes and silent regressions.
Scan large codebases, detect hotspots, and refactor code safely.
Validate JSON, emails, and other inputs for agents and applications.