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amansingh0311

MCP Qdrant Server with OpenAI Embeddings

带有 OpenAI 嵌入的 MCP Qdrant 服务器

该 MCP 服务器使用 Qdrant 矢量数据库和 OpenAI 嵌入提供矢量搜索功能。

特征

  • 使用 OpenAI 嵌入在 Qdrant 集合中进行语义搜索

  • 列出可用的集合

  • 查看收藏信息

Related MCP server: Qdrant MCP Server

先决条件

  • 已安装 Python 3.10+

  • Qdrant 实例(本地或远程)

  • OpenAI API 密钥

安装

  1. 克隆此存储库:

    git clone https://github.com/yourusername/mcp-qdrant-openai.git
    cd mcp-qdrant-openai
  2. 安装依赖项:

    pip install -r requirements.txt

配置

设置以下环境变量:

  • OPENAI_API_KEY :您的 OpenAI API 密钥

  • QDRANT_URL :您的 Qdrant 实例的 URL(默认值:“ http://localhost:6333 ”)

  • QDRANT_API_KEY :您的 Qdrant API 密钥(如果适用)

用法

直接运行服务器

python mcp_qdrant_server.py

使用 MCP CLI 运行

mcp dev mcp_qdrant_server.py

在 Claude Desktop 中安装

mcp install mcp_qdrant_server.py --name "Qdrant-OpenAI"

可用工具

查询集合

使用带有 OpenAI 嵌入的语义搜索来搜索 Qdrant 集合。

  • collection_name :要搜索的 Qdrant 集合的名称

  • query_text :自然语言的搜索查询

  • limit :返回的最大结果数(默认值:5)

  • model :要使用的 OpenAI 嵌入模型(默认值:text-embedding-3-small)

列表集合

列出 Qdrant 数据库中所有可用的集合。

collection_info

获取有关特定集合的信息。

  • collection_name :要获取信息的集合的名称

Claude Desktop 中的示例用法

一旦在 Claude Desktop 中安装完毕,您就可以使用如下工具:

What collections are available in my Qdrant database?

Search for documents about climate change in my "documents" collection.

Show me information about the "articles" collection.
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