What is Mcp Qdrant Openai

mcp-qdrant-openai is an MCP server that integrates Qdrant vector database capabilities with OpenAI embeddings to enable semantic search functionalities.

Use cases

Use cases include searching for documents in a Qdrant collection, retrieving information about specific collections, and performing semantic searches based on natural language queries.

How to use

To use mcp-qdrant-openai, clone the repository, install the required dependencies, configure the necessary environment variables, and run the server either directly or using the MCP CLI.

Key features

Key features include semantic search in Qdrant collections using OpenAI embeddings, listing available collections, and viewing collection information.

Where to use

mcp-qdrant-openai can be used in various fields such as data analysis, information retrieval, and natural language processing applications.

MCP Qdrant Server with OpenAI Embeddings

This MCP server provides vector search capabilities using Qdrant vector database and OpenAI embeddings.

Features

• Semantic search in Qdrant collections using OpenAI embeddings
• List available collections
• View collection information

Prerequisites

• Python 3.10+ installed
• Qdrant instance (local or remote)
• OpenAI API key

Installation

Installing via Smithery

To install Qdrant Vector Search Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @amansingh0311/mcp-qdrant-openai --client claude

Manual Installation

1. Clone this repository:

   git clone https://github.com/yourusername/mcp-qdrant-openai.git
   cd mcp-qdrant-openai
   

2. Install dependencies:

   pip install -r requirements.txt
   

Configuration

Set the following environment variables:

• OPENAI_API_KEY: Your OpenAI API key
• QDRANT_URL: URL to your Qdrant instance (default: “http://localhost:6333”)
• QDRANT_API_KEY: Your Qdrant API key (if applicable)

Usage

Run the server directly

python mcp_qdrant_server.py

Run with MCP CLI

mcp dev mcp_qdrant_server.py

Installing in Claude Desktop

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

Available Tools

query_collection

Search a Qdrant collection using semantic search with OpenAI embeddings.

• collection_name: Name of the Qdrant collection to search
• query_text: The search query in natural language
• limit: Maximum number of results to return (default: 5)
• model: OpenAI embedding model to use (default: text-embedding-3-small)

list_collections

List all available collections in the Qdrant database.

collection_info

Get information about a specific collection.

• collection_name: Name of the collection to get information about

Example Usage in Claude Desktop

Once installed in Claude Desktop, you can use the tools like this:

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.