Refactor code intelligently with automated testing, safety validation, and rollback capabilities. Enhance code readability, maintainability, and performance while ensuring high safety standards.
Analyze git changes using specified LLM models to review code for task/feature/bugfix alignment, security, performance, and coding standards, tailored to project context.
Analyze code for security vulnerabilities, performance issues, and quality standards. Get automated scoring and improvement recommendations across multiple files.
Analyze code for security, performance, and maintainability issues, providing actionable fixes, risk scoring, and automated suggestions to improve code quality.
Analyze code for issues and improvements using AI-powered code review. Submit code with language specification to receive detailed feedback on potential bugs, optimizations, and best practices.
An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.
Enables AI assistants to review GitLab merge requests by fetching diffs, analyzing code changes, adding comments, and managing approvals through the GitLab API. Supports comprehensive merge request analysis and version comparison for automated code review workflows.