qdrant/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
Configuration is done via environment variables. The only command-line argument is --transport, used to select the transport protocol.
> [!NOTE]
> You cannot provide both QDRANT_URL and QDRANT_LOCAL_PATH at the same time.
| 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 |
| QDRANT_SEARCH_LIMIT | Maximum number of results to return from search | 10 |
| QDRANT_READ_ONLY | Enable read-only mode (disables qdrant-store tool) | false |
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_LOG_LEVEL | Set logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL) | INFO |
| FASTMCP_SERVER_DEBUG | Enable debug mode | false |
| FASTMCP_SERVER_HOST | Host address to bind the server to | 127.0.0.1 |
| FASTMCP_SERVER_PORT | Port to run the server on | 8000 |
| FASTMCP_SERVER_ON_DUPLICATE_RESOURCES | Behavior for duplicate resources (warn, error, replace, ignore) | warn |
| FASTMCP_SERVER_ON_DUPLICATE_TOOLS | Behavior for duplicate tools (warn, error, replace, ignore) | warn |
| FASTMCP_SERVER_ON_DUPLICATE_PROMPTS | Behavior for duplicate prompts (warn, error, replace, ignore) | warn |
| FASTMCP_SERVER_DEPENDENCIES | List of dependencies to install in the server environment | [] |