This tool serves as an MCP (Model Context Protocol) server, providing AI assistants with private and cost-efficient access to machine learning textbook content. It transforms authoritative ML textbooks into a knowledge service, leveraging local LLMs (Qwen) and embeddings (sentence-transformers) to create a RAG (Retrieval Augmented Generation) system. By adhering to the MCP standard, it enables universal access and seamless integration of book knowledge directly into various AI clients like Claude Desktop and VS Code, fostering composability and future-proofing workflows.