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Qdrant MCP Server

by Jimmy974

An MCP server for interacting with Qdrant vector database. It provides tools for managing vectors, performing similarity searches, and automatic text-to-vector embedding using the MCP framework.

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What is Qdrant MCP Server?

Qdrant MCP Server is a tool that allows you to interact with a Qdrant vector database using the Master Control Program (MCP) framework. It provides functionalities for managing vectors, performing similarity searches, and automatically converting text into vector embeddings.

How to use Qdrant MCP Server?

To use the server, you can either run it locally or with Docker. First, configure the connection settings in a .env file. Then, install the package using pip install -e . and run the server with qdrant-mcp-server. Alternatively, build a Docker image and run the container, providing the necessary environment variables for Qdrant connection.

Key features of Qdrant MCP Server

  • Automatic text-to-vector embedding using FastEmbed

  • Store and retrieve text content with vector search

  • Use default collection configuration through environment variables

  • Text similarity search by content

Use cases of Qdrant MCP Server

  • Semantic search

  • Question answering

  • Document retrieval

  • Recommendation systems

FAQ from Qdrant MCP Server

What is Qdrant?

Qdrant is a vector database for storing and searching high-dimensional vectors.

What is FastEmbed?

FastEmbed is a library used for efficient text embedding.

How do I configure the Qdrant connection?

You can configure the Qdrant connection settings using environment variables such as QDRANT_HOST, QDRANT_PORT, and QDRANT_API_KEY.

How do I run the tests?

Install development dependencies using pip install -e "[dev]" and then run the tests using pytest -xvs tests/.

How do I disable SSL verification?

Set QDRANT_VERIFY_SSL=False in your .env file or when running the Docker container if your Qdrant server uses a self-signed certificate.