Public Health Application

A comprehensive public health monitoring and analysis system built with FastAPI, LangGraph agents, and MCP (Model Context Protocol) servers.

🏗️ Project Structure

public-health-app/
├── .vscode/                    # VS Code workspace configuration
│   ├── launch.json            # Debug configurations for all components
│   ├── tasks.json             # Build and run tasks
│   ├── settings.json          # Workspace settings
│   └── extensions.json        # Recommended extensions
├── backend/
│   ├── app/                   # Main FastAPI application
│   │   ├── agents/           # LangGraph intelligent agents
│   │   │   ├── health_dashboard_agent.py
│   │   │   ├── test_dashboard_agent.py
│   │   │   ├── demo_dashboard_agent.py
│   │   │   └── README_LANGGRAPH_AGENT.md
│   │   ├── routers/          # FastAPI route handlers
│   │   ├── models/           # Data models
│   │   └── main.py           # FastAPI application entry point
│   └── mcp/                   # MCP servers and infrastructure
│       ├── mcp_public_health.py  # FastMCP public health server
│       ├── venv/              # Python virtual environment
│       └── requirements.txt   # Python dependencies
├── .env-template              # Environment variables template
└── README.md                  # This file

🚀 Quick Start

1. Setup Environment

# Copy environment template
cp .env-template .env

# Edit .env with your configuration
# Add API keys for OpenAI/Anthropic if desired

# Activate virtual environment
cd backend/mcp
source venv/bin/activate

2. Start Services

Option A: Using VS Code Tasks (Recommended)

• Open Command Palette (Cmd+Shift+P)
• Run Tasks: Run Task
• Select "Start FastMCP Server"
• Optionally run "Start FastAPI App"

Option B: Command Line

# Start FastMCP server (terminal 1)
cd backend/mcp
source venv/bin/activate
python3 -m uvicorn mcp_public_health:app --host 0.0.0.0 --port 8001

# Start FastAPI app (terminal 2)
cd backend
source mcp/venv/bin/activate
python3 start_fastapi.py

3. Test the Agents

# Navigate to agents directory
cd backend/app/agents

# Run the dashboard agent tests
PYTHONPATH=../../mcp:../.. python3 test_dashboard_agent.py

# Try the example usage
PYTHONPATH=../../mcp:../.. python3 example_usage.py

4. Test the Dashboard API

# Test the dashboard endpoints (requires both servers running)
cd backend
python3 test_dashboard_api.py

🔧 VS Code Integration

The workspace includes comprehensive VS Code configurations:

Debug Configurations

• Debug FastMCP Server: Debug the MCP server
• Debug Dashboard Agent: Debug the LangGraph agent interactively
• Debug Dashboard Agent Tests: Debug the test suite
• Debug FastAPI App: Debug the main web application

Tasks

• Start FastMCP Server: Launch the MCP server
• Start FastAPI App: Launch the web application
• Run Dashboard Agent Tests: Execute agent test suite
• Install Dependencies: Install Python packages

Usage

1. Open the workspace in VS Code
2. Press F5 to see debug options
3. Use Cmd+Shift+P → "Tasks: Run Task" for build tasks
4. Recommended extensions will be suggested automatically

🧪 Development Workflow

1. Agent Development

cd backend/app/agents
PYTHONPATH=../../mcp:../.. python3 health_dashboard_agent.py interactive

2. MCP Server Development

cd backend/mcp
source venv/bin/activate
python3 mcp_public_health.py

3. Web API Development

cd backend
source mcp/venv/bin/activate
python3 start_fastapi.py

📚 Key Components

LangGraph Agents (backend/app/agents/)

Intelligent agents built with LangGraph for health data analysis:

• PublicHealthDashboardAgent: Generates executive dashboards
• Supports OpenAI GPT-4 and Anthropic Claude
• Comprehensive test suite and demo examples

FastMCP Server (backend/mcp/)

Model Context Protocol server providing health data tools:

• Public health alerts retrieval
• Health risk trends analysis
• RESTful API with SSE transport

FastAPI Application (backend/app/)

Web application providing REST APIs:

• Health data endpoints
• Agent integration APIs
• Modern async Python architecture

🔌 API Endpoints

• FastAPI App: http://localhost:8000 (configurable via FASTAPI_HOST and FASTAPI_PORT)

  • API docs: http://localhost:8000/docs
  • Health check: http://localhost:8000/health
  • Dashboard endpoints:
    • POST /dashboard/generate - Generate custom dashboard
    • GET /dashboard/status - Check agent status
    • GET /dashboard/alerts-summary - Alerts-focused dashboard
    • GET /dashboard/trends-summary - Trends-focused dashboard
    • GET /dashboard/emergency-summary - Emergency response dashboard
    • POST /dashboard/generate/async - Async dashboard generation

• FastMCP Server: http://localhost:8001

  • SSE endpoint: http://localhost:8001/sse
  • Health check: http://localhost:8001/health

🌟 Features

• Multi-LLM Support: OpenAI GPT-4, Anthropic Claude
• Real-time Data: Live health alerts and trends
• Intelligent Analysis: AI-powered pattern recognition
• Modern Architecture: FastAPI, LangGraph, MCP protocol
• Developer Experience: VS Code integration, comprehensive testing

📖 Documentation

• LangGraph Agent Documentation
• Dashboard API Documentation
• FastMCP Server Documentation
• MCP Protocol Documentation

🤝 Contributing

1. Use the VS Code workspace for development
2. Follow the established project structure
3. Add tests for new features
4. Update documentation as needed

📄 License

See project license for details.