Cover image
Try Now
2025-03-23

使用QDRANT矢量数据库进行语义搜索的MCP服务器

3 years

Works with Finder

1

Github Watches

4

Github Forks

0

Github Stars

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

相关推荐

  • NiKole Maxwell
  • I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • Yasir Eryilmaz
  • AI scriptwriting assistant for short, engaging video content.

  • Alexandru Strujac
  • Efficient thumbnail creator for YouTube videos

  • Daren White
  • A supportive coach for mastering all Spanish tenses.

  • J. DE HARO OLLE
  • Especialista en juegos de palabras en varios idiomas.

  • albert tan
  • Japanese education, creating tailored learning experiences.

  • Beniyam Berhanu
  • Therapist adept at identifying core issues and offering practical advice with images.

  • apappascs
  • 发现市场上最全面,最新的MCP服务器集合。该存储库充当集中式枢纽,提供了广泛的开源和专有MCP服务器目录,并提供功能,文档链接和贡献者。

  • ShrimpingIt
  • MCP系列GPIO Expander的基于Micropython I2C的操作,源自ADAFRUIT_MCP230XX

  • huahuayu
  • 统一的API网关,用于将多个Etherscan样区块链Explorer API与对AI助手的模型上下文协议(MCP)支持。

  • deemkeen
  • 用电源组合控制您的MBOT2:MQTT+MCP+LLM

  • zhaoyunxing92
  • MCP(消息连接器协议)服务

  • pontusab
  • 光标与风浪冲浪社区,查找规则和MCP

    Reviews

    5 (1)
    Avatar
    user_q2lwKa1B
    2025-04-16

    As a dedicated user of mcp applications, I must say that mcp-server-qdrant-retrieve by gergelyszerovay has significantly streamlined my server processes. The seamless integration and ease of use make it a standout choice for anyone looking to enhance their retrieval systems. Highly recommended!