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.
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.
pip install mcp-server-qdrantAdd this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"qdrant-mcp-server-qdrant-github": {
"command": "uvx",
"args": [
"pip install mcp-server-qdrant"
]
}
}
}Restart Claude Desktop, then ask:
"What tools do you have available from qdrant?"
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 |
"What resources are available in qdrant?"
Claude will query available resources and return a list of what you can access.
"Show me details about [specific item] in qdrant"
Claude will fetch and display detailed information about the requested item.
"Create a new [item] in qdrant with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
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