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Qdrant Retrieve MCP Server

@gergelyszerovay

代码仓库

基本信息

分类

数据库

许可证

MIT license

传输方式

stdio

作者

gergelyszerovay

关于 Qdrant Retrieve MCP Server

MCP server for semantic search with Qdrant vector database

#qdrant#semantic-search#mcp-server

Qdrant Retrieve MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Qdrant Retrieve MCP Server 工具

1

Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queries

概览

What is Qdrant Retrieve MCP Server?

An MCP server that enables semantic search across multiple Qdrant vector database collections. It supports multi-query input, configurable result counts, and collection source tracking, connecting to any Qdrant instance specified by URL.

How to use Qdrant Retrieve MCP Server?

Configure it in Claude Desktop by adding an MCP server entry with the command npx -y @gergelyszerovay/mcp-server-qdrant-retrive and optionally set the QDRANT_API_KEY environment variable. Alternatively, run it from the command line using flags like --qdrantUrl, --enableHttpTransport, or --embeddingModelType.

Key features of Qdrant Retrieve MCP Server

  • Semantic search across multiple Qdrant collections
  • Multi-query support (array of query texts)
  • Configurable result count (topK)
  • Collection source tracking in results
  • Stdio and HTTP transport options
  • Optional REST API server

Use cases of Qdrant Retrieve MCP Server

  • Retrieve semantically similar documents from multiple Qdrant collections in one request
  • Integrate semantic search into AI assistants via the MCP protocol
  • Power applications that need multi-query document retrieval with similarity scores
  • Combine vector search with LLM tools for knowledge retrieval

常见问题

1

What embedding model does the server use?

The default embedding model is `Xenova/all-MiniLM-L6-v2`. It can be customized via the `--embeddingModelType` command-line option.

2

How do I connect to my Qdrant instance?

Set the Qdrant URL using the `--qdrantUrl` option (default: `http://localhost:6333`). If authentication is required, provide an API key via the `QDRANT_API_KEY` environment variable.

3

Why is the first retrieval slow?

The first retrieve may be slower because the server downloads the required embedding model on initial use.

4

Can the server run over HTTP instead of stdio?

Yes, enable HTTP transport with the `--enableHttpTransport` flag. The MCP HTTP server port defaults to 3001.

5

What transport methods are available?

The server supports stdio transport (enabled by default), HTTP transport (optional), and a REST API server (optional, default port 3002).

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