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graphrag-mcp

Combines Neo4j and Qdrant databases for document search with semantic relevance and context, serving as a powerful MCP server for structured and vector search.

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About this tool

graphrag-mcp

Repository: https://github.com/rileylemm/graphrag_mcp

Category: data-access-integration-mcp-servers

Tags: mcp, semantic-search, vector-database, neo4j, qdrant

Description

graphrag-mcp is a Model Context Protocol (MCP) server designed to interact with a hybrid graph and vector database system, combining Neo4j (graph database) and Qdrant (vector database). It enables structured and semantic document search, making it suitable for applications needing both graph-based and semantic retrieval.

Features

  • Hybrid Retrieval System: Combines Neo4j for structured graph queries and Qdrant for semantic vector-based search.
  • MCP Server: Implements the Model Context Protocol specification, allowing compatibility with any MCP-enabled client.
  • LLM Integration: Seamlessly integrates with large language models by providing a hybrid retrieval backend.
  • Search Tools:
    • search_documentation: Performs semantic search for information.
    • hybrid_search: Executes both semantic and graph-based search approaches.
  • Easy Setup:
    • Configuration via .env file for database connections.
    • Quick start scripts and detailed setup instructions provided.
  • Extensible: Can be added as a resource to MCP clients such as Cursor and Claude Desktop.
  • Document Indexing: Supports indexing documents into both Neo4j and Qdrant databases.
  • Open Source: Licensed under the MIT License.

Pricing

No pricing information provided. The project is open source under the MIT License.

License

MIT License.

Attribution

If you use or adapt this MCP server, attribution to Riley Lemm and a link back to the repository is requested.

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Information

Websitegithub.com
PublishedMay 14, 2025

Categories

1 Item
Data Access & Integration Mcp Servers

Tags

5 Items
#mcp
#semantic-search
#vector-database
#neo4j
#qdrant

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