Analyze code quality by checking for issues and providing improvement suggestions with detailed metrics to enhance code maintainability and reliability.
Analyze code for security, performance, and maintainability issues, providing actionable fixes, risk scoring, and automated suggestions to improve code quality.
Validate input data for optimization problems, ensuring accuracy by checking for errors, warnings, and providing suggestions. Supports diverse problem types and structured data input.
Analyze GitHub repositories to provide AI-powered improvement suggestions for code modernization, performance, maintainability, and security with actionable refactoring recommendations.
Bridges Xcode and Cursor to provide real-time access to build errors, warnings, and debug output from Xcode's DerivedData, enabling automated error analysis and fixes directly within Cursor.
CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments
Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.