MemPalace/mempalace
MemPalace is an open-source, local-first AI memory system that stores and retrieves conversation history verbatim using semantic search, supporting pluggable backends like ChromaDB and integrating ...
Awesome MCP › Knowledge & Memory
hannesrudolph/mcp-ragdocs
The project "mcp-ragdocs" is an implementation of an MCP (Model Context Protocol) server designed to enhance AI assistants by enabling them to retrieve and process documentation through advanced vector search and semantic context augmentation techniques. This server allows AI models to augment their responses with relevant, contextually appropriate documentation, improving the quality and accuracy of the information provided. Key features of the project include vector-based documentation search and retrieval, support for multiple documentation sources, semantic search capabilities, automated documentation processing, and real-time context augmentation for large language models (LLMs). The server provides several tools such as search_documentation, which allows natural language queries to search through stored documentation and returns relevant excerpts ranked by relevance; list_sources, which lists all documentation sources currently indexed; extract_urls, which crawls web pages to extract and optionally queue URLs for processing; remove_documentation, which permanently removes documentation sources by URL; list_queue, which shows URLs waiting to be processed; run_queue, which processes and indexes queued URLs; and clear_queue, which clears the processing queue. The project is particularly useful for building documentation-aware AI assistants, creating context-aware developer tools, implementing semantic documentation search, and augmenting existing knowledge bases. It integrates with tools like Claude Desktop and requires environment variables such as OPENAI_API_KEY for embeddings generation and QDRANT_URL and QDRANT_API_KEY for connecting to a Qdrant vector database instance. Licensed under the MIT License, this project is a fork of the original mcp-ragdocs by qpd-v, providing a robust foundation for enhancing AI assistant capabilities through semantic documentation retrieval and processing.
https://github.com/hannesrudolph/mcp-ragdocs
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