# Clone the repository
git clone https://github.com/your-username/A2A-MCP-RealEstate.git
cd A2A-MCP-RealEstate

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\\Scripts\\activate

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env
# Edit .env file with your API keys

# .env file
MOLIT_API_KEY=your_molit_api_key_here
NAVER_CLIENT_ID=your_naver_client_id_here
NAVER_CLIENT_SECRET=your_naver_client_secret_here
PORT=8080
AGENT_ID=agent-py-001
AGENT_NAME=A2A_Python_Agent
LOG_LEVEL=INFO
ENVIRONMENT=development

# Start the web server
python runner.py

# Access the web interface
open http://localhost:8080/web/

# Real Estate Recommendation MCP Server
python app/mcp/real_estate_recommendation_mcp.py

# Location Service MCP Server
python app/mcp/location_service.py

{
  "mcpServers": {
    "korean-realestate": {
      "command": "python",
      "args": ["app/mcp/real_estate_recommendation_mcp.py"],
      "cwd": "/path/to/A2A-MCP-RealEstate"
    }
  }
}

📁 A2A-MCP-RealEstate/
├── 📂 app/
│   ├── 📂 mcp/                    # FastMCP Servers
│   │   ├── 🏠 real_estate_recommendation_mcp.py  # Main recommendation server
│   │   └── 📍 location_service.py                # Location analysis server
│   ├── 📂 routes/                 # Web API Routes
│   │   ├── 🌐 web_routes.py       # Web interface routes
│   │   └── 🔧 mcp_routes.py       # MCP API routes
│   ├── 📂 utils/                  # Utilities
│   │   ├── 🔌 mcp_client.py       # MCP client utilities
│   │   ├── ⚙️ config.py           # Configuration management
│   │   └── 📝 logger.py           # Logging utilities
│   ├── 📂 templates/              # HTML Templates
│   │   ├── 🏠 index.html          # Home page
│   │   ├── 🧪 mcp_test.html       # MCP testing interface
│   │   ├── 🤖 agent_test.html     # Agent testing interface
│   │   └── 📊 result templates    # Result display templates
│   └── 📄 main.py                 # FastAPI application
├── 📄 runner.py                   # Application runner
├── 📄 requirements.txt            # Python dependencies
├── 📄 task.md                     # Development tasks
└── 📄 README.md                   # This file

# Start the MCP server
python app/mcp/real_estate_recommendation_mcp.py

# The server will be available for MCP clients
# Example tools: get_real_estate_data, recommend_property, etc.

# Start web server
python runner.py

# Navigate to http://localhost:8080/web/
# 1. Go to "MCP 테스트" for data query testing
# 2. Go to "Agent 테스트" for property recommendation

import httpx

# Get apartment trade data
response = await httpx.post("http://localhost:8080/web/api/mcp/test", json={
    "tool_name": "get_real_estate_data",
    "parameters": {
        "lawd_cd": "11680",  # Gangnam-gu, Seoul
        "deal_ymd": "202401",  # January 2024
        "property_type": "아파트"
    }
})