
Project-scoped Qdrant MCP server with hybrid search and configurable collections
Inspired by claude-qdrant-mcp with enhanced project detection, Python implementation, and flexible collection management.
workspace-qdrant-mcp provides intelligent vector database operations through the Model Context Protocol (MCP), featuring automatic project detection, hybrid search capabilities, and configurable collection management for seamless integration with Claude Desktop and Claude Code.
Prerequisites
Qdrant server must be running - workspace-qdrant-mcp connects to Qdrant for vector operations.
- Local: Default
http://localhost:6333
- Cloud: Requires
QDRANT_API_KEY
environment variable
For local installation, see the Qdrant repository. For documentation examples, we assume the default local setup.
Installation
# Install globally with uv (recommended)
uv tool install workspace-qdrant-mcp
# Or with pip
pip install workspace-qdrant-mcp
After installation, run the setup wizard:
workspace-qdrant-setup
This interactive wizard will guide you through configuration, test your setup, and get you ready to use the MCP server with Claude in minutes.
For development setup, see CONTRIBUTING.md.
MCP Integration
Claude Desktop
Add to your claude_desktop_config.json
:
{
"mcpServers": {
"workspace-qdrant-mcp": {
"command": "workspace-qdrant-mcp",
"env": {
"QDRANT_URL": "http://localhost:6333",
"COLLECTIONS": "project",
"GLOBAL_COLLECTIONS": "docs,references"
}
}
}
}
Claude Code
claude mcp add workspace-qdrant-mcp
Configure environment variables through Claude Code's settings or your shell environment.
Configuration
Environment Variables
Variable | Default | Description |
---|---|---|
QDRANT_URL |
http://localhost:6333 |
Qdrant server URL |
QDRANT_API_KEY |
(none) | Required for Qdrant cloud, optional for local |
COLLECTIONS |
project |
Collection suffixes (comma-separated) |
GLOBAL_COLLECTIONS |
(none) | Global collection names (comma-separated) |
GITHUB_USER |
(none) | Filter projects by GitHub username |
FASTEMBED_MODEL |
sentence-transformers/all-MiniLM-L6-v2 |
Embedding model (see options below) |
Embedding Model Options
Choose the embedding model that best fits your system resources and quality requirements:
Lightweight (384D) - Good for limited resources:
sentence-transformers/all-MiniLM-L6-v2
(default) - Fast, low memory
Balanced (768D) - Better quality, moderate resources:
BAAI/bge-base-en-v1.5
- Excellent for most use casesjinaai/jina-embeddings-v2-base-en
- Good multilingual supportthenlper/gte-base
- Google's T5-based model
High Quality (1024D) - Best results, high resource usage:
BAAI/bge-large-en-v1.5
- Top performance for Englishmixedbread-ai/mxbai-embed-large-v1
- Latest state-of-the-art
Configuration example:
# Use a more powerful model
export FASTEMBED_MODEL="BAAI/bge-base-en-v1.5"
# Or in Claude Desktop config
"env": {
"FASTEMBED_MODEL": "BAAI/bge-base-en-v1.5"
}
Collection Naming
Collections are automatically created based on your project and configuration:
Project Collections:
COLLECTIONS="project"
→ creates{project-name}-project
COLLECTIONS="scratchbook,docs"
→ creates{project-name}-scratchbook
,{project-name}-docs
Global Collections:
GLOBAL_COLLECTIONS="docs,references"
→ createsdocs
,references
Example: For project "my-app" with COLLECTIONS="scratchbook,docs"
:
my-app-scratchbook
(project-specific notes)my-app-docs
(project-specific documentation)docs
(global documentation)references
(global references)
Usage
Interact with your collections through natural language commands in Claude:
Store Information:
- "Store this note in my project scratchbook: [your content]"
- "Add this document to my docs collection: [document content]"
Search & Retrieve:
- "Search my project for information about authentication"
- "Find all references to the API endpoint in my scratchbook"
- "What documentation do I have about deployment?"
Hybrid Search:
- Combines semantic search (meaning-based) with keyword search (exact matches)
- Automatically optimizes results using reciprocal rank fusion (RRF)
- Searches across project and global collections
CLI Tools
Interactive Setup Wizard
Get up and running in minutes with the guided setup wizard:
# Interactive setup with guided prompts
workspace-qdrant-setup
# Advanced mode with all configuration options
workspace-qdrant-setup --advanced
# Non-interactive mode for automation
workspace-qdrant-setup --non-interactive
The setup wizard:
- Tests Qdrant connectivity and validates configuration
- Helps choose optimal embedding models
- Configures Claude Desktop integration automatically
- Creates sample documents for immediate testing
- Provides final system verification
Diagnostics and Testing
Comprehensive troubleshooting and health monitoring:
# Full system diagnostics
workspace-qdrant-test
# Test specific components
workspace-qdrant-test --component qdrant
workspace-qdrant-test --component embedding
# Include performance benchmarks
workspace-qdrant-test --benchmark
# Generate detailed report
workspace-qdrant-test --report diagnostic_report.json
Health Monitoring
Real-time system health and performance monitoring:
# One-time health check
workspace-qdrant-health
# Continuous monitoring with live dashboard
workspace-qdrant-health --watch
# Detailed analysis with optimization recommendations
workspace-qdrant-health --analyze
# Generate health report
workspace-qdrant-health --report health_report.json
Collection Management
Use wqutil
for collection management and administration:
# List collections
wqutil list-collections
# Collection information
wqutil collection-info my-project-scratchbook
# Validate configuration
workspace-qdrant-validate
# Check workspace status
wqutil workspace-status
Document Ingestion
Batch process documents for immediate searchability:
# Ingest documents from a directory
workspace-qdrant-ingest /path/to/docs --collection my-project
# Process specific formats only
workspace-qdrant-ingest /path/to/docs -c my-project -f pdf,md
# Preview what would be processed (dry run)
workspace-qdrant-ingest /path/to/docs -c my-project --dry-run
Documentation
- API Reference - Complete MCP tools documentation
- Contributing Guide - Development setup and guidelines
- Benchmarking - Performance testing and metrics
Troubleshooting
Quick Diagnostics:
# Run comprehensive system diagnostics
workspace-qdrant-test
# Get real-time health status
workspace-qdrant-health
# Run setup wizard to reconfigure
workspace-qdrant-setup
Connection Issues:
# Test Qdrant connectivity specifically
workspace-qdrant-test --component qdrant
# Verify Qdrant is running
curl http://localhost:6333/collections
# Validate complete configuration
workspace-qdrant-validate
Performance Issues:
# Run performance benchmarks
workspace-qdrant-test --benchmark
# Monitor system resources
workspace-qdrant-health --watch
# Get optimization recommendations
workspace-qdrant-health --analyze
Collection Issues:
# List current collections
wqutil list-collections
# Check project detection
wqutil workspace-status
For detailed troubleshooting, see API.md.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Related Projects:
- claude-qdrant-mcp - Original TypeScript implementation
- Qdrant - Vector database
- FastMCP - MCP server framework