Q

Qdrant Docs Rag

Real-time documentation context through vector-based search and retrieval via Qdrant.

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Updated Nov 22, 2025
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Real-time documentation context through vector-based search and retrieval via Qdrant.
  1. Obtain your OpenAI API Key

    • Go to the OpenAI platform: https://platform.openai.com/api-keys.
    • Log in with your OpenAI account.
    • Click on “Create new secret key.”
    • Copy the generated API key. You will need this value for OPENAI_API_KEY.
  2. Set up your Qdrant vector database

    • If you don’t have a Qdrant instance, deploy one:
    • Copy the URL of your Qdrant instance (e.g., https://<your-instance>.qdrant.tech). You will need this value for QDRANT_URL.
  3. Obtain your Qdrant API Key

    • If you use Qdrant Cloud:
      • In the Qdrant Cloud interface, open your project.
      • Navigate to the “API Keys” section.
      • Click “Create API Key,” give it a name, and copy the generated API key. Use this for QDRANT_API_KEY.
    • If you run a local/self-hosted instance without authentication, you may leave this blank or configure authentication as per the Qdrant documentation.
  4. Fill values in the FastMCP connection interface

    • Press the “Install Now” button for the MCP server.
    • In the FastMCP connection interface, provide the following values:
      • OPENAI_API_KEY: (the key copied from OpenAI)
      • QDRANT_URL: (the URL to your Qdrant instance)
      • QDRANT_API_KEY: (the key copied from Qdrant Cloud, or leave blank if not required)
  5. Save your changes

    • Click “Save” or “Connect” in the interface to apply your configuration.

How to Install Qdrant Docs Rag

Install Qdrant Docs Rag MCP server with one click through FastMCP. Choose your preferred AI development tool below:

Claude Desktop

Click "Claude Desktop" in Quick Start

Cursor IDE

Click "Cursor IDE" in Quick Start

VS Code

Click "VS Code" in Quick Start

Quick Start

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