GraphRAG MCP Server

Name: GraphRAG MCP Server
Author: rileylemm

@rileylemm

代码仓库

关于 GraphRAG MCP Server

This is a MCP server I built to interact with my hybrid graph rag db.

#graphdb #vector-db #mcp-server

基本信息

分类

其他

许可证

MIT

运行时

python

传输方式

stdio

发布者

rileylemm

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "graphrag_mcp": {
      "command": "uv",
      "args": [
        "run",
        "main.py"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is GraphRAG MCP Server?

A Model Context Protocol (MCP) server that queries a hybrid graph and vector database system combining Neo4j (graph database) and Qdrant (vector database). Built for developers integrating large language models with powerful semantic and graph-based document retrieval.

How to use GraphRAG MCP Server?

Clone the repository, install dependencies with uv install, configure Neo4j and Qdrant connection details in a .env file, then run uv run main.py. For MCP client integration, add the server to your mcp.json configuration file (e.g., for Claude Desktop or Cursor) pointing to the run_server.sh script.

Key features of GraphRAG MCP Server

Semantic search through document embeddings
Graph-based context expansion following relationships
Hybrid search combining vector similarity with graph links
MCP tools and resources for LLM integration
Full documentation of Neo4j schema and Qdrant collection info

Use cases of GraphRAG MCP Server

Enabling LLMs to perform semantic document retrieval
Expanding context using graph relationships for richer answers
Hybrid search that balances vector similarity with structured graph queries
Integrating Neo4j‑ and Qdrant‑backed knowledge into Claude Desktop or Cursor

FAQ from GraphRAG MCP Server

What are the runtime requirements?

Python 3.12+, plus a running Neo4j instance on localhost:7687 and a running Qdrant instance on localhost:6333 (default ports). Documents must be already indexed in both databases.

How do I install the server?

Clone the repository, run uv install to install dependencies, set database credentials in .env, then start with uv run main.py. A run_server.sh script is provided for MCP client registration.

Why am I getting empty results?

Ensure your document collection is properly indexed in both Neo4j and Qdrant. Verify database connectivity and that the QDRANT_COLLECTION name in .env matches your indexed collection.

How do I configure authentication for Neo4j and Qdrant?

Set NEO4J_USER, NEO4J_PASSWORD, and optionally NEO4J_URI (default bolt://localhost:7687) in .env. Qdrant authentication is not explicitly covered; the default configuration assumes no auth.

What transports and authentication does the server use?

The server uses the MCP protocol over HTTP/WebSocket (native). Neo4j communicates via Bolt protocol, Qdrant via HTTP. Credentials for Neo4j are read from environment variables. No MCP‑level auth is described.