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Integrate multi-agent AI into IDEs for coding, review, optimization, and security checks.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CodeMentor-AI" yet — see the docs or source repo.
Analyze this Python service code in the IDE. First identify potential bugs and performance bottlenecks, then provide a refactored version, explain the changes through adversarial peer review, and finally flag any security risks.
A list of issues, refactored code, review feedback, and a security risk summary.
Review the changes in this pull request. Check for logic errors, maintainability issues, insufficient test coverage, and potential vulnerabilities, then rank recommendations by severity.
A structured PR review with issue categories, priorities, and fix recommendations.
Optimize this authentication and authorization module without changing behavior. Improve readability and performance, and focus on injection, privilege escalation, and secret leakage risks.
Optimized code, readability and performance improvements, and a security assessment conclusion.
Review code, suggest refactors, and generate tests with AI assistance.
Simulate a multi-agent engineering team to review code for quality and risks.
Get intelligent, context-aware code reviews and improvement suggestions with MCP.
Review repositories in natural language for security, performance, and code quality issues
Search and navigate multiple code repositories with natural language understanding.
Query multiple AI models for code reviews, debates, and diverse perspectives.