# MCP Qdrant Server with OpenAI Embeddings
[](https://smithery.ai/server/@amansingh0311/mcp-qdrant-openai)
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](https://smithery.ai/server/@amansingh0311/mcp-qdrant-openai):
```bash
npx -y @smithery/cli install @amansingh0311/mcp-qdrant-openai --client claude
```
### Manual Installation
1. Clone this repository:
```bash
git clone https://github.com/yourusername/mcp-qdrant-openai.git
cd mcp-qdrant-openai
```
2. Install dependencies:
```bash
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
```bash
python mcp_qdrant_server.py
```
### Run with MCP CLI
```bash
mcp dev mcp_qdrant_server.py
```
### Installing in Claude Desktop
```bash
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.
```
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