Qdrant MCP Server
About This Server
The official Qdrant MCP server. Lets AI agents directly operate the Qdrant vector database: create and search collections, insert vector data, and perform semantic search — no manual API requests needed.
Installation
npx -y @qdrant/mcp-server-qdrantOfficial README installation guide
Using uvx
When using uvx no specific installation is needed to directly run *mcp-server-qdrant*.
QDRANT_URL="http://localhost:6333" \
COLLECTION_NAME="my-collection" \
EMBEDDING_MODEL="sentence-transformers/all-MiniLM-L6-v2" \
uvx mcp-server-qdrantTransport Protocols
The server supports different transport protocols that can be specified using the --transport flag:
QDRANT_URL="http://localhost:6333" \
COLLECTION_NAME="my-collection" \
uvx mcp-server-qdrant --transport sseSupported transport protocols:
stdio(default): Standard input/output transport, might only be used by local MCP clientssse: Server-Sent Events transport, perfect for remote clientsstreamable-http: Streamable HTTP transport, perfect for remote clients, more recent than SSE
The default transport is stdio if not specified.
When SSE transport is used, the server will listen on the specified port and wait for incoming connections. The default
port is 8000, however it can be changed using the FASTMCP_SERVER_PORT environment variable.
QDRANT_URL="http://localhost:6333" \
COLLECTION_NAME="my-collection" \
FASTMCP_SERVER_PORT=1234 \
uvx mcp-server-qdrant --transport sseUsing Docker
A Dockerfile is available for building and running the MCP server:
# Build the container
docker build -t mcp-server-qdrant .
# Run the container
docker run -p 8000:8000 \
-e FASTMCP_SERVER_HOST="0.0.0.0" \
-e QDRANT_URL="http://your-qdrant-server:6333" \
-e QDRANT_API_KEY="your-api-key" \
-e COLLECTION_NAME="your-collection" \
mcp-server-qdrant> [!TIP]
> Please note that we set FASTMCP_SERVER_HOST="0.0.0.0" to make the server listen on all network interfaces. This is
> necessary when running the server in a Docker container.
Installing via Smithery
To install Qdrant MCP Server for Claude Desktop automatically via Smithery:
npx @smithery/cli install mcp-server-qdrant --client claudeManual configuration of Claude Desktop
To use this server with the Claude Desktop app, add the following configuration to the "mcpServers" section of your
claude_desktop_config.json:
{
"qdrant": {
"command": "uvx",
"args": ["mcp-server-qdrant"],
"env": {
"QDRANT_URL": "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333",
"QDRANT_API_KEY": "your_api_key",
"COLLECTION_NAME": "your-collection-name",
"EMBEDDING_MODEL": "sentence-transformers/all-MiniLM-L6-v2"
}
}
}For local Qdrant mode:
{
"qdrant": {
"command": "uvx",
"args": ["mcp-server-qdrant"],
"env": {
"QDRANT_LOCAL_PATH": "/path/to/qdrant/database",
"COLLECTION_NAME": "your-collection-name",
"EMBEDDING_MODEL": "sentence-transformers/all-MiniLM-L6-v2"
}
}
}This MCP server will automatically create a collection with the specified name if it doesn't exist.
By default, the server will use the sentence-transformers/all-MiniLM-L6-v2 embedding model to encode memories.
For the time being, only FastEmbed models are supported.
Frequently Asked Questions
What can Qdrant MCP do?
Lets AI agents directly operate the Qdrant vector database: create and manage collections, insert and update vector data, perform semantic similarity search, and manage indexes and filters. Ideal for building RAG (Retrieval-Augmented Generation) apps, semantic search, and recommendation systems.
Does Qdrant MCP need a Qdrant instance?
Yes, it needs a running Qdrant instance (either local Docker deployment or Qdrant Cloud). The MCP server connects via the Qdrant client API and requires the instance URL and API key (if applicable) to be configured.
Is Qdrant MCP free?
The MCP server itself is open source and free (Apache 2.0). Qdrant offers an open source version (self-hosted, free) and Qdrant Cloud (free tier available, usage-based billing beyond).