bookMCPServer

The Book MCP Server with Vector Database is a robust solution for semantic search within large text documents, such as books. It leverages the power of FAISS (Facebook AI Similarity Search) to efficiently handle large sets of vectors, enabling quick retrieval of semantically similar text chunks. The server processes a text document by splitting it into manageable chunks, generating embeddings for each chunk using Sentence Transformers, and storing these embeddings in a FAISS index. This setup is a prime example of a Retrieval Augmented Generation (RAG) component, where the server acts as a retriever, fetching relevant context based on user queries. The server exposes an HTTP endpoint that accepts search queries via the Model Context Protocol (MCP), making it easy to integrate with other applications and services. This project is particularly useful for developers looking to implement advanced search capabilities in their applications, providing a scalable and efficient solution for text retrieval tasks.