Qdrant Vector Database Server
Store and retrieve information efficiently using a Qdrant vector database. Leverage semantic search capabilities to find relevant data quickly and easily. Integrate with FastEmbed for enhanced text embeddings and configure effortlessly with environment variables.
Installation
Installing for Claude Desktop
Option 1: One-Command Installation
npx mcpbar@latest install Jimmy974/mcp-server-qdrant -c claude
This command will automatically install and configure the Qdrant Vector Database Server MCP server for your selected client.
Option 2: Manual Configuration
Run the command below to open your configuration file:
npx mcpbar@latest edit -c claude
After opening your configuration file, copy and paste this configuration:
View JSON configuration
{
"mcpServers": {
"Qdrant Vector Database Server": {
"command": "uvx",
"args": [
"mcp-server-qdrant"
],
"env": {
"QDRANT_URL": "${input:qdrant_url}",
"QDRANT_API_KEY": "${input:qdrant_api_key}"
}
}
}
}
MCP Server for Qdrant
A Machine Control Protocol (MCP) server for storing and retrieving information from a Qdrant vector database.
Features
- Store text information with optional metadata in Qdrant
- Semantic search for stored information
- FastEmbed integration for text embeddings
- Environment-based configuration
- Docker support
Installation
Using pip
pip install mcp-server-qdrant
From source
git clone https://github.com/your-org/mcp-server-qdrant.git
cd mcp-server-qdrant
make setup
Configuration
Configuration is done through environment variables. You can create a .env
file based on the .env.example
file:
cp .env.example .env
Edit the .env
file to configure the server:
# Qdrant configuration
QDRANT_URL=http://localhost:6333
QDRANT_API_KEY=your-api-key
# Collection name
COLLECTION_NAME=memories
# Embedding provider configuration
EMBEDDING_PROVIDER=fastembed
EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
Usage
Running locally
python -m mcp_server_qdrant.main
Or using the make command:
make run
Docker
docker-compose up
Tools
The MCP server provides the following tools:
qdrant-store
Stores information in the Qdrant database.
information: The text to store
metadata: Optional JSON metadata to associate with the text
qdrant-find
Searches for information in the Qdrant database using semantic search.
query: The search query
Development
Testing
make test
Formatting
make format
Linting
make lint
Building
make build
License
Apache License 2.0
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