MCP Server for Qdrant
by Jimmy974
The MCP Server for Qdrant is a server that stores and retrieves information from a Qdrant vector database using the Machine Control Protocol (MCP). It allows for semantic search and includes FastEmbed integration.
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What is MCP Server for Qdrant?
The MCP Server for Qdrant is a server application designed to interact with a Qdrant vector database. It provides an interface to store, search, and retrieve information using the Machine Control Protocol (MCP). It leverages vector embeddings for semantic search capabilities.
How to use MCP Server for Qdrant?
To use the server, first install it using pip or from source. Configure the server using environment variables in a .env file, specifying the Qdrant URL, API key, collection name, and embedding provider. Run the server locally using python -m mcp_server_qdrant.main or make run, or deploy it using Docker with docker-compose up. Use the qdrant-store tool to store information and the qdrant-find tool to perform semantic searches.
Key features of MCP Server for Qdrant
Store text information with optional metadata in Qdrant
Semantic search for stored information
FastEmbed integration for text embeddings
Environment-based configuration
Docker support
Use cases of MCP Server for Qdrant
Storing and retrieving knowledge base articles
Implementing a chatbot with semantic search capabilities
Building a recommendation system based on text similarity
Creating a system for analyzing and categorizing documents
FAQ from MCP Server for Qdrant
What is Qdrant?
What is Qdrant?
Qdrant is a vector similarity search engine.
What is FastEmbed?
What is FastEmbed?
FastEmbed is a library for generating text embeddings.
How do I configure the server?
How do I configure the server?
Configuration is done through environment variables in a .env file.
How do I store information in Qdrant?
How do I store information in Qdrant?
Use the qdrant-store tool with the information and optional metadata.
How do I search for information in Qdrant?
How do I search for information in Qdrant?
Use the qdrant-find tool with the search query.