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
克隆此存储库:
git clone https://github.com/yourusername/mcp-qdrant-openai.git cd mcp-qdrant-openai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.This server cannot be deployed
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