qdrant
pipVerifiedThe Qdrant MCP server exposes Qdrant's vector search capabilities to AI agents. It provides tools for embedding generation, vector storage, and similarity search. The server connects directly to Qdrant's vector database API. Developers use it to integrate vector search into AI workflows, enabling semantic search, recommendation systems, and anomaly detection.
1,1852250Updated 3 months ago
Overview
The Qdrant MCP server exposes Qdrant's vector search capabilities to AI agents. It provides tools for embedding generation, vector storage, and similarity search. The server connects directly to Qdrant's vector database API. Developers use it to integrate vector search into AI workflows, enabling semantic search, recommendation systems, and anomaly detection.
Installation
1Install the package
pip
pip install mcp-server-qdrant2Add to Claude
Add this configuration to your claude_desktop_config.json:
claude_desktop_config.json
{
"mcpServers": {
"qdrant-mcp-server-qdrant-github": {
"command": "uvx",
"args": [
"pip install mcp-server-qdrant"
]
}
}
}3Verify installation
Restart Claude Desktop, then ask:
"What tools do you have available from qdrant?"
Prerequisites
- Python 3.10 or higher
- pip or uv package manager
- Claude Desktop or Claude API access
- API key for qdrant
Configuration
API Key Required
This server requires an API key from qdrant. Add it to your environment or config.
| Variable | Required | Description |
|---|---|---|
| QDRANT_API_KEY | Yes | Your qdrant API key |
Usage Examples
List Resources
"What resources are available in qdrant?"
Claude will query available resources and return a list of what you can access.
Get Details
"Show me details about [specific item] in qdrant"
Claude will fetch and display detailed information about the requested item.
Create New
"Create a new [item] in qdrant with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
Works with qdrant
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