Why this server?
This server provides RAG (Retrieval-Augmented Generation) capabilities, enabling semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, which fits the 'chat with RAG' query.
Alicense-quality-maintenanceProvides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.Last updated1116Why this server?
This server provides RAG (Retrieval Augmented Generation) over your Apple Notes, providing a way to chat with your apple notes.
Flicense-qualityDmaintenanceEnables semantic search and RAG (Retrieval Augmented Generation) over your Apple Notes.Last updated188382Why this server?
This server provides vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management which provides underlying infrastructure to implement RAG.
AlicenseAqualityDmaintenanceA Model Context Protocol server providing vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage.Last updated641Why this server?
This server is a primitive RAG implementation that runs locally which enables chat with local RAG resources.
AlicenseAqualityBmaintenance"primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨Last updated5122PythonMITWhy this server?
This server enables AI assistants to augment their responses with relevant documentation context via retrieval and processing documentation through vector search, enabling a retrieval augmented generation implementation.
Alicense-qualityDmaintenanceA Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.Last updated1133MITWhy this server?
This server provides the necessary components for RAG, including using Ollama or OpenAI to generate embeddings.
Alicense-qualityBmaintenanceAn MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. Uses Ollama or OpenAI to generate embeddings. Docker files includedLast updated3328MITWhy this server?
This server enables retrieval of data from Ragie's Knowledge Base. Ragie enables the user to build vector databases and connect to existing vector databases (including Qdrant, Pinecone and Chroma).
Alicense-quality-maintenanceAn MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.Last updated2787Why this server?
This server can be used to implement a RAG application using the Qdrant vector database.

mcp-server-qdrantofficial
AlicenseBquality-maintenanceThis repository is an example of how to create a MCP server for Qdrant, a vector search engine.Last updated21,370Why this server?
This server provides a robust API for storing, retrieving, and managing text-based memories with semantic search capabilities which enables RAG.
Flicense-qualityCmaintenanceModel Context Protocol (MCP) server implementation for semantic search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic search capabilities. You can use Claude and Cline AI AlsoLast updated14