Qdrant Retrieve MCP Server

MCP server for semantic search with Qdrant vector database.

Features

Semantic search across multiple collections
Multi-query support
Configurable result count
Collection source tracking

Note: The server connects to a Qdrant instance specified by URL.

Note 2: The first retrieve might be slower, as the MCP server downloads the required embedding model.

API

Tools

qdrant_retrieve
- Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queries
- Inputs:
  - collectionNames (string[]): Names of the Qdrant collections to search across
  - topK (number): Number of top similar documents to retrieve (default: 3)
  - query (string[]): Array of query texts to search for
- Returns:
  - results: Array of retrieved documents with:
    - query: The query that produced this result
    - collectionName: Collection name that this result came from
    - text: Document text content
    - score: Similarity score between 0 and 1

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "qdrant": {
      "command": "npx",
      "args": ["-y", "@gergelyszerovay/mcp-server-qdrant-retrive"],
      "env": {
        "QDRANT_API_KEY": "your_api_key_here"
      }
    }
  }
}

Command Line Options

MCP server for semantic search with Qdrant vector database.

Options
  --enableHttpTransport      Enable HTTP transport [default: false]
  --enableStdioTransport     Enable stdio transport [default: true]
  --enableRestServer         Enable REST API server [default: false]
  --mcpHttpPort=<port>       Port for MCP HTTP server [default: 3001]
  --restHttpPort=<port>      Port for REST HTTP server [default: 3002]
  --qdrantUrl=<url>          URL for Qdrant vector database [default: http://localhost:6333]
  --embeddingModelType=<type> Type of embedding model to use [default: Xenova/all-MiniLM-L6-v2]
  --help                     Show this help message

Environment Variables
  QDRANT_API_KEY            API key for authenticated Qdrant instances (optional)

Examples
  $ mcp-qdrant --enableHttpTransport
  $ mcp-qdrant --mcpHttpPort=3005 --restHttpPort=3006
  $ mcp-qdrant --qdrantUrl=http://qdrant.example.com:6333
  $ mcp-qdrant --embeddingModelType=Xenova/all-MiniLM-L6-v2

API

Tools

qdrant_retrieve

Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queries
Inputs:
- collectionNames (string[]): Names of the Qdrant collections to search across
- topK (number): Number of top similar documents to retrieve (default: 3)
- query (string[]): Array of query texts to search for
Returns:
- results: Array of retrieved documents with:
  - query: The query that produced this result
  - collectionName: Collection name that this result came from
  - text: Document text content
  - score: Similarity score between 0 and 1

{ "mcpServers": { "qdrant": { "command": "npx", "args": ["-y", "@gergelyszerovay/mcp-server-qdrant-retrive"], "env": { "QDRANT_API_KEY": "your_api_key_here" } } } }

Command Line Options

MCP server for semantic search with Qdrant vector database. Options --enableHttpTransport Enable HTTP transport [default: false] --enableStdioTransport Enable stdio transport [default: true] --enableRestServer Enable REST API server [default: false] --mcpHttpPort=<port> Port for MCP HTTP server [default: 3001] --restHttpPort=<port> Port for REST HTTP server [default: 3002] --qdrantUrl=<url> URL for Qdrant vector database [default: http://localhost:6333] --embeddingModelType=<type> Type of embedding model to use [default: Xenova/all-MiniLM-L6-v2] --help Show this help message Environment Variables QDRANT_API_KEY API key for authenticated Qdrant instances (optional) Examples $ mcp-qdrant --enableHttpTransport $ mcp-qdrant --mcpHttpPort=3005 --restHttpPort=3006 $ mcp-qdrant --qdrantUrl=http://qdrant.example.com:6333 $ mcp-qdrant --embeddingModelType=Xenova/all-MiniLM-L6-v2