MCP Development Environment
Execute SQL queries on a PostgreSQL database, enabling data retrieval and manipulation.
Perform cache set and get operations on a Redis instance for caching and data storage.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Development Environmentlist files in the data directory"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Development Environment
A comprehensive Docker-based development environment for building and testing Model Context Protocol (MCP) servers.
๐ฏ What's Included
Core Services:
Python MCP Server (Port 8000) - Full-featured implementation with debugging
Node.js MCP Server (Port 3000) - Alternative implementation
PostgreSQL (Port 5432) - Database with sample data
Redis (Port 6379) - Caching layer
Nginx File Server (Port 8080) - Static file serving with CORS
Development Features:
Hot reloading for both Python and Node.js
Built-in debugger support (Python: 5678, Node.js: 9229)
Comprehensive logging and monitoring
Pre-configured testing frameworks
Sample data and schemas
Code quality tools (linting, formatting, type checking)
Related MCP server: Enhanced MCP Server
๐ Quick Start
Setup the environment:
# Make the setup script executable and run it
chmod +x setup.sh
./setup.shVerify everything is working:
# Check service status
docker-compose ps
# Test endpoints
curl http://localhost:8080/health # File server
curl http://localhost:8000/health # Python MCP server
curl http://localhost:3000/health # Node.js MCP serverStart developing:
# Edit the Python MCP server
vim src/main.py
# View logs in real-time
docker-compose logs -f mcp-server
# Run tests
docker-compose exec mcp-server python -m pytest๐ง Key Features of the MCP Servers
Available Tools:
write_file- Write content to filesexecute_sql- Run database queriescache_set/get- Redis cache operationslist_directory- Browse file systemanalyze_data- Basic data analysis on CSV files
Resources:
File system access to
/datadirectoryDatabase table schemas and sample data
Configuration files and documentation
Sample Usage:
# The Python server provides tools for:
await mcp_server.call_tool("write_file", {
"path": "analysis.txt",
"content": "Sample analysis results"
})
await mcp_server.call_tool("execute_sql", {
"query": "SELECT * FROM users WHERE department = $1",
"parameters": ["Engineering"]
})๐ Debugging Setup
Python (VSCode):
{
"name": "Python: Remote Attach",
"type": "python",
"request": "attach",
"connect": {"host": "localhost", "port": 5678},
"pathMappings": [
{"localRoot": "${workspaceFolder}/src", "remoteRoot": "/app/src"}
]
}Node.js (Chrome DevTools):
Open
chrome://inspectConnect to
localhost:9229
๐ Monitoring & Logs
# View all service logs
docker-compose logs -f
# Monitor specific service
docker-compose logs -f mcp-server
# Check resource usage
docker stats
# Database operations
docker-compose exec postgres psql -U mcp_user -d mcp_dev
# Redis operations
docker-compose exec redis redis-cli๐ ๏ธ Development Workflow
The environment supports both transport methods:
stdio (default) - For direct MCP client integration
HTTP/WebSocket - For web-based development and testing
You can easily switch between implementations or run both simultaneously for comparison and testing.
๐๏ธ Project Structure
mcp/
โโโ src/ # Python MCP server source
โ โโโ main.py # Main Python server implementation
โโโ src-node/ # Node.js MCP server source
โ โโโ server.js # Main Node.js server implementation
โโโ db/ # Database initialization scripts
โ โโโ init.sql # Schema and tables
โ โโโ sample_data.sql # Sample data
โโโ data/ # Data files (mounted to containers)
โโโ static/ # Static files served by Nginx
โโโ tests/ # Test suites
โโโ .vscode/ # VSCode debug configuration
โโโ docker-compose.yml # Service definitions
โโโ python.Dockerfile # Python server container
โโโ node.Dockerfile # Node.js server container
โโโ nginx.conf # Nginx configuration
โโโ setup.sh # Setup and management script
โโโ README.md # This file๐ง Management Commands
The setup.sh script provides convenient management:
./setup.sh setup # Initial setup and start (default)
./setup.sh start # Start services
./setup.sh stop # Stop services
./setup.sh restart # Restart services
./setup.sh status # Show service status
./setup.sh logs # Show service logs
./setup.sh clean # Remove everything (with confirmation)
./setup.sh help # Show help๐งช Testing
Both Python and Node.js servers include comprehensive test suites:
# Run Python tests
docker-compose exec mcp-server python -m pytest tests/ -v
# Run Node.js tests
docker-compose exec mcp-server-node npm test
# Run tests with coverage
docker-compose exec mcp-server python -m pytest tests/ --cov=src๐ Database Schema
The PostgreSQL database includes several sample tables:
users- User accounts with departments and rolesproducts- Product catalog with categories and inventoryorders- Order history with status trackingorder_items- Order line itemsanalytics_events- Event tracking dataapp_config- Application configuration
๐ก API Endpoints
File Server (Port 8080):
GET /health- Health checkGET /data/- Browse data directoryGET /static/- Browse static filesGET /api/docs- API documentation
Python MCP Server (Port 8000):
GET /health- Health checkMCP protocol via stdio transport
Node.js MCP Server (Port 3000):
GET /health- Health checkMCP protocol via stdio transport
๐จ Troubleshooting
Services not starting:
Check Docker is running:
docker infoCheck port conflicts:
netstat -tulpn | grep :8000View startup logs:
docker-compose logs
Database connection issues:
# Test database connectivity
docker-compose exec postgres pg_isready -U mcp_user
# Connect to database manually
docker-compose exec postgres psql -U mcp_user -d mcp_devRedis connection issues:
# Test Redis connectivity
docker-compose exec redis redis-cli pingDebug not working:
Ensure debug ports (5678, 9229) are not in use
Check firewall settings
Verify VSCode debug configuration matches container setup
๐ค Contributing
Fork the repository
Make changes in your environment
Test thoroughly with provided test suites
Submit a pull request
๐ License
This project is provided as-is for development and testing purposes.
This environment gives you a complete MCP development platform with real databases, caching, file systems, and debugging tools - perfect for building and testing production-ready MCP servers!
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