Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.
Intelligent learning sidecar for AI coding assistants. Helps developers learn from AI-generated code changes through interactive blocking quizzes and provides agents with persistent project-specific debugging memory using silent RAG tools. Features 56% token optimization and multi-language support.
Multi-LLM deliberation with anonymized peer review. Runs a 3-stage council: parallel responses → anonymous ranking → synthesis. Based on Andrej Karpathy's LLM Council concept.