Provides AI assistants with intelligent access to ML textbook content through RAG-powered search, chapter retrieval, and documentation generation capabilities. Uses local models for privacy-focused, source-grounded responses from indexed technical books.
Creates and searches private, local RAG libraries from documentation to ground AI assistants in authoritative sources, reducing hallucinations by providing current, accurate context from your own docs instead of relying on outdated training data.
Enables AI models to seamlessly access and query local markdown technical documentation files, providing automatic documentation context without explicit prompting.
Enables AI assistants to crawl, index, and retrieve information from technical documentation using semantic search, with optional knowledge graph validation for code hallucination detection.
Enables AI assistants to search, read, and retrieve context from local knowledge bases with full-text search, absolute paths, and section-level details.
A local MCP server that gives AI coding assistants retrieval access to your personal knowledge base of books, standards, and docs, grounding their answers in sources you trust.
