How do I use Qdrant Retrieve MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type `@` followed by the MCP server name and your instructions, e.g., "`@Qdrant Retrieve MCP Server` search for documents about machine learning and neural networks in the research and papers collections" That's it! The server will respond to your query, and you can continue using it as needed. Here is a [step-by-step guide with screenshots](https://glama.ai/blog/2025-07-08-how-to-install-and-use-mcp-servers).

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.

Related MCP server: Better Qdrant MCP Server

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