mcp-server-qdrant: A Qdrant MCP server
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Overview
A basic Model Context Protocol server for keeping and retrieving memories in the Qdrant vector search engine. It acts as a semantic memory layer on top of the Qdrant database.
Components
Tools
qdrant-store- Store some information in the Qdrant database
- Input:
information(string): Information to storemetadata(JSON): Optional metadata to store
- Returns: Confirmation message
qdrant-find- Retrieve relevant information from the Qdrant database
- Input:
query(string): Query to use for searching
- Returns: Information stored in the Qdrant database as separate messages
Environment Variables
The configuration of the server is done using environment variables:
| Name | Description LLM applications require external data sources and tools to function effectively. This repository provides an example of how to create a Model Context Protocol (MCP) server for Qdrant, a vector search engine. It acts as a semantic memory layer on top of the Qdrant database. The server supports different transport protocols that can be specified using the --transport flag. The default transport is stdio if not specified. A Dockerfile is available for building and running the MCP server. To install Qdrant MCP Server for Claude Desktop automatically via Smithery: npx @smithery/cli install mcp-server-qdrant --client claude. To use this server with the Claude Desktop app, add the following configuration to the "mcpServers" section of your claude_desktop_config.json.
