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Store and retrieve vector-based memories for AI systems.

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5 installs
Updated Nov 22, 2025
Not audited
Store and retrieve vector-based memories for AI systems.
  1. Create or Access a Qdrant Account

    • If you do not have a Qdrant Cloud account, go to the Qdrant Cloud and sign up.
    • Log in to your Qdrant Cloud dashboard.
  2. Create a New Qdrant Cluster or Access an Existing One

    • On the Qdrant Cloud dashboard, either create a new cluster or select an existing one you wish to use.
    • Copy the HTTPS endpoint URL for this cluster (it looks like https://xyz-example.region.aws.cloud.qdrant.io:6333).
  3. Obtain an API Key for Your Qdrant Cluster

    • In the sidebar, navigate to the “API Keys” section (sometimes called “API Access”).
    • Click “Generate API Key” or “Create New Key”.
    • Optionally, provide a name and select the desired permissions (Read/Write or as required).
    • Save the generated API key securely. You will need it for configuration.
  4. Choose or Create a Collection Name

    • Decide on a collection name for storing your vectors (e.g., my-collection). This can be any string and will be used to organize your data.
    • You can use an existing collection name or specify a new one; mcp-server-qdrant will create it if it does not exist.
  5. (Optional) Decide on an Embedding Model

    • By default, sentence-transformers/all-MiniLM-L6-v2 is used.
    • You can change the model if needed, but for most users, the default is sufficient.
  6. Fill In the FastMCP Connection Interface

    • Click the Install Now button in your environment to open the FastMCP connection interface.
    • In the fields provided, enter:
      • QDRANT_URL: Your cluster URL from step 2, e.g., https://xyz-example.region.aws.cloud.qdrant.io:6333
      • QDRANT_API_KEY: Your API key from step 3
      • COLLECTION_NAME: The collection name you chose in step 4
      • (Optional) EMBEDDING_MODEL: Change only if you wish to use a different model.
  7. Save and Complete the Setup

    • Confirm and save your configuration in the FastMCP connection interface.
    • You are now ready to use the Qdrant MCP server with your specified settings.

Note:

  • If you are using a local Qdrant server instead of Qdrant Cloud, set QDRANT_URL to your local Qdrant endpoint (e.g. http://localhost:6333).
  • For local mode, you may omit QDRANT_API_KEY if authentication is not enabled and set QDRANT_LOCAL_PATH instead if running Qdrant locally.

How to Install Qdrant

Install Qdrant 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

Qdrant is an officially maintained MCP server, verified by the FastMCP team.

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