Q

Qdrant MCP Server

Store and search vector embeddings with Qdrant from AI agents.

open-source 70/100 AI & Machine Learning qdrant vector-database embeddings semantic-search rag ai

A Model Context Protocol server for Qdrant vector database. Enables AI agents to store, search, and manage vector embeddings for semantic search and retrieval-augmented generation.

Supports collection management, point upsert, similarity search with filtering, and payload management for building RAG applications.

Install

pip install mcp-server-qdrant

MCP Client Config

{
  "mcpServers": {
    "qdrant": {
      "command": "python",
      "args": [
        "-m",
        "mcp_server_qdrant"
      ],
      "env": {
        "QDRANT_URL": "http://localhost:6333",
        "QDRANT_API_KEY": "<your-api-key>"
      }
    }
  }
}

Required Environment Variables

  • QDRANT_URL

Capabilities

Tools

create_collectionupsert_pointssearchdelete_collectionget_point

Compatible With

Claude Desktop Claude Code Cursor Windsurf

Pricing

Server and Qdrant are free. Qdrant Cloud available for managed hosting.

Metrics

920

GitHub Stars

7,500

Installs

580

Weekly

3

Open Issues

View Repository By Qdrant

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