Qdrant MCP Server

Search vector embeddings, manage collections, and run hybrid semantic search in Qdrant.

Official Repository / Source Documentation

What it does

Enables conversational AI agents to interact directly with Qdrant vector database. Create collections, upsert vector embeddings, query nearest neighbors, and filter payloads for advanced RAG architectures.

Installation & Setup

Level: advanced

```json
{
  "mcpServers": {
    "qdrant": {
      "command": "npx",
      "args": ["-y", "@qdrant/mcp-server-qdrant"],
      "env": { "QDRANT_URL": "https://your-cluster.qdrant.io", "QDRANT_API_KEY": "your_key" }
    }
  }
}
```

Prerequisites: Qdrant instance (local Docker or Qdrant Cloud).

Security & Privacy Notes

Secure vector DB communication using TLS and cluster API keys.

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