Qdrant

Official

Implement semantic memory layer on top of the Qdrant vector search engine

About Qdrant MCP Server

The Qdrant MCP server provides a comprehensive interface for AI applications to interact with qdrant features. It enables AI assistants to help with various tasks related to data workflows.

Features

Tools
Resources

Category

Data
Getting Started

To use the Qdrant MCP server in your AI application, follow these steps:

  1. Install the MCP client SDK for your platform
  2. Connect to the Qdrant MCP server
  3. Authenticate with your Qdrant credentials
  4. Start using the tools, resources, and prompts provided by the server

Example Code


// Connect to the Qdrant MCP server
const server = await mcp.connect("qdrant");

// Authenticate
await server.authenticate();

// Use a tool
const result = await server.tools.listRepositories({
  // Parameters
});

// Access a resource
const resource = await server.resources.repositoryContent({
  // Parameters
});

// Use a prompt
const response = await server.prompts.summarizePR({
  // Parameters
});
                      
Installation

npm

npm install @mcp/server-qdrant

pip

pip install mcp-server-qdrant
Compatible With
Claude for Desktop
Perplexity
Cursor
MCP Agent Framework