{"repo":"rileylemm/graphrag_mcp","free":true,"listed":false,"github":"https://github.com/rileylemm/graphrag_mcp","clone":"git clone https://github.com/rileylemm/graphrag_mcp.git","description":"This is a MCP server I built to interact with my hybrid graph rag db.","language":"Python","stars":63,"topics":[],"license":"MIT","category":"mcp-servers","readme_excerpt":"GraphRAG MCP Server A Model Context Protocol server for querying a hybrid graph and vector database system, combining Neo4j (graph database) and Qdrant (vector database) for powerful semantic and graph-based document retrieval. Overview GraphRAG MCP provides a seamless integration between large language models and a hybrid retrieval system that leverages the strengths of both graph databases (Neo4j) and vector databases (Qdrant). This enables: - Semantic search through document embeddings - Graph-based context expansion following relationships - Hybrid search combining vector similarity with graph relationships - Full integration with Claude and other LLMs through MCP This project follows the Model Context Protocol specification, making it compatible with any MCP-enabled client. Features - Semantic search using sentence embeddings and Qdrant - Graph-based context expansion using Neo4j - Hybrid search combining both approaches - MCP tools and resources for LLM integration - Full documentation of Neo4j schema and Qdrant collection information Prerequisites - Python 3.12+ - Neo4j running on localhost:7687 (default configuration) - Qdrant running on localhost:6333 (default configuration) - Document data indexed in both databases Installation Quick Start 1. Clone this repository: 2. Install dependencies with uv: 3. Configure your database connections in the .env file: 4. Run the server: Detailed Setup Guide For a detailed guide on setting up the underlying hybrid database system, ","default_branch":null,"files":null,"tree":[],"storefront":"/r/rileylemm","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/rileylemm/graphrag_mcp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}