Q

Qdrant Retrieve

Enables semantic search across multiple document collections using Qdrant vector database integratio...

138 views
0 installs
Updated Sep 10, 2025
Not audited
Enables semantic search across multiple document collections using Qdrant vector database integration, allowing natural language queries with configurable result counts and collection tracking.
  1. Log in to your Qdrant Dashboard or Server

    • Access your Qdrant Cloud account at https://cloud.qdrant.io/, or, if self-hosted, access your Qdrant server’s admin/configuration interface.
  2. Navigate to the API Keys Section

    • In Qdrant Cloud, go to your project or cluster.
    • Open the “API Keys” tab or section (may be listed under “Access,” “Security,” or “Settings”).
  3. Generate a New API Key

    • Click on “Create API Key,” “Generate Key,” or similar.
    • Choose appropriate permissions (typically, “Read/Write” or the permissions needed for the MCP server to access collections and perform semantic searches).
  4. Copy the API Key

    • After creation, copy the API key shown. It will only be displayed once.
  5. Add the API Key in FastMCP

    • Click the “Install Now” button for the Qdrant integration in your FastMCP interface.
    • In the connection setup form, locate the field for QDRANT_API_KEY.
    • Paste the API key you copied from the Qdrant dashboard.
  6. Enter the Qdrant URL (if needed)

    • If your Qdrant server is not running at the default URL (http://localhost:6333), enter the correct value for qdrantUrl in the connection form.
  7. Save and Test the Connection

    • Confirm and save your configuration.
    • Optionally, test the integration to ensure the MCP server can access Qdrant successfully.

Quick Start

View on GitHub

More for Database

View All →

More for AI and Machine Learning

View All →

Similar MCP Servers

B

Better Qdrant

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.

Database AI and Machine Learning
116
0
Q

Qdrant Docs Rag

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

AI and Machine Learning Developer Tools
149
0

Report Issue

Thank you! Your issue report has been submitted successfully.