Qdrant MCP Server is the official Model Context Protocol implementation for Qdrant, enabling LLM applications to store and retrieve semantic memories through a vector search engine. It transforms unstructured information into vector embeddings for intelligent, meaning-based search and recall. Key features: - Store information as vector embeddings with optional JSON metadata - Semantic similarity search to retrieve contextually relevant memories based on meaning - Support for both Qdrant Cloud (via URL and API key) and local Qdrant deployments (via local path) - Configurable embedding providers for automatic text vectorization - Collection management with support for default and custom collection names - Persistent semantic memory layer that maintains context across conversations

mcp-server-qdrant: A Qdrant MCP server

[](https://smithery.ai/protocol/mcp-server-qdrant)

> 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

An official 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

1. qdrant-store - Store some information in the Qdrant database - Input: - information (string): Information to store - metadata (JSON): Optional metadata to store - collection_name (string): Name of the collection to store the information in. This field is required if there are no default collection name. If there is a default collection name, this field is not enabled. - Returns: Confirmation message 2. qdrant-find - Retrieve relevant information from the Qdrant database - Input: - query (string): Query to use for searching - collection_name (string): Name of the collection to store the information in. This field is required if there are no default collection name. If there is a default collection name, this field is not enabled. - Returns: Information stored in the Qdrant database as separate messages

Environment Variables

The configuration of the server is done using environment variables:

| Name | Description | Default Value | |--------------------------|---------------------------------------------------------------------|-------------------------------------------------------------------| | QDRANT_URL | URL of the Qdrant server | None | | QDRANT_API_KEY | API key for the Qdrant server | None | | COLLECTION_NAME | Name of the default collection to use. | None | | QDRANT_LOCAL_PATH | Path to the local Qdrant database (alternative to QDRANT_URL) | None | | EMBEDDING_PROVIDER | Embedding provider to use (currently only "fastembed" is supported) | fastembed | | EMBEDDING_MODEL | Name of the embedding model to use | sentence-transformers/all-MiniLM-L6-v2 | | TOOL_STORE_DESCRIPTION | Custom description for the store tool | See default in settings.py | | TOOL_FIND_DESCRIPTION | Custom description for the find tool | See default in settings.py |

Note: You cannot provide both QDRANT_URL and QDRANT_LOCAL_PATH at the same time.

> [!IMPORTANT] > Command-line arguments are not supported anymore! Please use environment variables for all configuration.

FastMCP Environment Variables

Since mcp-server-qdrant is based on FastMCP, it also supports all the FastMCP environment variables. The most important ones are listed below:

| Environment Variable | Description | Default Value | |---------------------------------------|-----------------------------------------------------------|---------------| | FASTMCP_DEBUG | Enable debug mode | false | | FASTMCP_LOG_LEVEL | Set logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL) | INFO | | FASTMCP_HOST | Host address to bind the server to | 127.0.0.1 | | FASTMCP_PORT | Port to run the server on | 8000 | | FASTMCP_WARN_ON_DUPLICATE_RESOURCES | Show warnings for duplicate resources | true | | FASTMCP_WARN_ON_DUPLICATE_TOOLS | Show warnings for duplicate tools | true | | FASTMCP_WARN_ON_DUPLICATE_PROMPTS | Show warnings for duplicate p