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Better Qdrant

Connects AI systems to Qdrant vector database for semantic search capabilities through multiple embe...

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Updated Sep 9, 2025
Not audited
Connects AI systems to Qdrant vector database for semantic search capabilities through multiple embedding services, enabling efficient document management and similarity searches without leaving the conversation interface.
  1. Obtain your Qdrant server URL and (if required) API key
    • If you are using a local Qdrant server, the URL is typically http://localhost:6333.
    • For remote Qdrant or managed cloud service, log in to your Qdrant host/provider and locate the HTTP endpoint and API key (if your deployment requires it).
  2. (If using OpenAI for embeddings) Get your OpenAI API key
  3. (If using OpenRouter for embeddings) Get your OpenRouter API key
  4. (If using a local Ollama instance for embeddings)
    • Ensure Ollama is installed and running locally. By default, the endpoint is http://localhost:11434.
    • No API key is needed for local Ollama.
  5. Fill in the FastMCP connection interface
    • Click the "Install Now" button for the Better Qdrant integration.
    • In the FastMCP interface, provide the values you collected:
      • QDRANT_URL (e.g., http://localhost:6333)
      • QDRANT_API_KEY (if required by your Qdrant instance; otherwise, leave empty)
      • OPENAI_API_KEY (if using OpenAI embeddings)
      • OPENROUTER_API_KEY (if using OpenRouter embeddings)
      • OLLAMA_ENDPOINT (if using a local Ollama server; defaults to http://localhost:11434)
  6. Save the configuration
    • Click "Save" or "Apply" in the FastMCP interface to store your environment variable values.

Note: Only the API keys for services you actually use are required; others may be left empty.

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