RAG and LLM
Manages and summarizes notes using a Model Context Protocol server, integrating Retrieval Augmented Generation (RAG) and Large Language Models (LLMs).
This Model Context Protocol (MCP) server serves as a powerful backend for integrating Retrieval Augmented Generation (RAG) and Large Language Model (LLM) functionalities. It provides a straightforward note storage system accessible via custom URIs, allowing users to store and manage text data. Key features include a "summarize-notes" prompt for intelligently summarizing all stored notes with customizable detail levels, and an "add-note" tool for dynamically updating the server's knowledge base. This enables applications like Claude Desktop to interactively leverage RAG and LLM for content summarization and management.
