Nitzan Pomerantz
488 lines
14 KiB
Markdown
488 lines
14 KiB
Markdown
# Israel Real Estate MCP
|
|
|
|
A Python-based Mission Control Program (MCP) for interacting with the Israeli government's public real estate data API (Govmap). This project provides both a Python library and an MCP server that allows real estate agents, professionals, and AI agents to query recent property deals, analyze market trends, and retrieve detailed real estate information.
|
|
|
|
## Description
|
|
|
|
This project provides a comprehensive Python interface to the Israeli government's Govmap API, enabling users to:
|
|
|
|
- Search for property addresses using autocomplete
|
|
- Find geographical coordinates for addresses
|
|
- Retrieve block (Gush) and parcel (Helka) information
|
|
- Query recent real estate deals by location
|
|
- Get detailed street and neighborhood deal information
|
|
- Analyze market trends in specific areas
|
|
|
|
## Features
|
|
|
|
- **Address Autocomplete**: Search for addresses using free text and get precise coordinates
|
|
- **Geospatial Data**: Retrieve block and parcel information for any coordinate point
|
|
- **Deal Discovery**: Find real estate deals within a specified radius of any location
|
|
- **Street Analysis**: Get detailed deal information for specific streets
|
|
- **Neighborhood Insights**: Analyze deals within entire neighborhoods
|
|
- **Time-based Filtering**: Search for deals within specific date ranges
|
|
- **Comprehensive Search**: High-level function that combines all features to find deals for any address
|
|
- **Error Handling**: Robust error handling for network issues and API failures
|
|
- **Logging**: Detailed logging for debugging and monitoring
|
|
|
|
## Installation
|
|
|
|
### Prerequisites
|
|
|
|
- Python 3.7 or higher
|
|
- pip package manager
|
|
|
|
### Setup Instructions
|
|
|
|
1. **Clone the repository:**
|
|
```bash
|
|
git clone <repository-url>
|
|
cd nadlan-mcp
|
|
```
|
|
|
|
2. **Create a virtual environment:**
|
|
```bash
|
|
python -m venv venv
|
|
```
|
|
|
|
3. **Activate the virtual environment:**
|
|
- On Windows:
|
|
```bash
|
|
venv\Scripts\activate
|
|
```
|
|
- On macOS/Linux:
|
|
```bash
|
|
source venv/bin/activate
|
|
```
|
|
|
|
4. **Install required packages:**
|
|
```bash
|
|
pip install -r requirements.txt
|
|
```
|
|
|
|
## Usage
|
|
|
|
### MCP Server (Recommended for AI Agents)
|
|
|
|
The project includes an MCP (Model Context Protocol) server that allows AI agents to access Israeli real estate data. The server provides multiple deployment options:
|
|
|
|
#### 1. Interactive Demo Server
|
|
|
|
For testing and demonstration purposes:
|
|
|
|
```bash
|
|
python simple_mcp_server.py
|
|
```
|
|
|
|
This runs an interactive demo where you can test the tools directly in the terminal.
|
|
|
|
#### 2. Full MCP Server
|
|
|
|
For production use with MCP clients:
|
|
|
|
```bash
|
|
python run_mcp_server.py
|
|
```
|
|
|
|
This starts the full MCP server that can be connected to by MCP-compatible clients.
|
|
|
|
#### 3. Direct Server Module
|
|
|
|
You can also run the server directly:
|
|
|
|
```bash
|
|
python -m nadlan_mcp.mcp_server
|
|
```
|
|
|
|
#### MCP Client Configuration
|
|
|
|
To connect to the server from MCP clients, use the following configuration:
|
|
|
|
**For Claude Desktop or other MCP clients:**
|
|
|
|
Add to your MCP client configuration:
|
|
|
|
```json
|
|
{
|
|
"servers": {
|
|
"nadlan-mcp": {
|
|
"command": "python",
|
|
"args": ["/path/to/nadlan-mcp/run_mcp_server.py"],
|
|
"env": {}
|
|
}
|
|
}
|
|
}
|
|
```
|
|
|
|
**For development with stdio transport:**
|
|
|
|
```python
|
|
import asyncio
|
|
from mcp.client.stdio import stdio_client
|
|
|
|
async def main():
|
|
async with stdio_client(["python", "run_mcp_server.py"]) as client:
|
|
# List available tools
|
|
result = await client.list_tools()
|
|
print("Available tools:", result.tools)
|
|
|
|
# Call a tool
|
|
result = await client.call_tool("find_recent_deals_for_address", {
|
|
"address": "סוקולוב 38 חולון",
|
|
"years_back": 2
|
|
})
|
|
print("Results:", result)
|
|
|
|
asyncio.run(main())
|
|
```
|
|
|
|
#### Available MCP Tools
|
|
|
|
The server provides these tools for AI agents:
|
|
|
|
##### 🏠 `find_recent_deals_for_address`
|
|
**Main comprehensive analysis tool**
|
|
- **Description**: Find all relevant real estate deals for a given address
|
|
- **Parameters**:
|
|
- `address` (required): The address to search for (Hebrew or English)
|
|
- `years_back` (optional): Number of years to look back (default: 2)
|
|
- **Returns**: List of deals with detailed information
|
|
|
|
**Example usage:**
|
|
```json
|
|
{
|
|
"address": "בן יהודה 1 תל אביב",
|
|
"years_back": 3
|
|
}
|
|
```
|
|
|
|
##### 📊 `analyze_market_trends`
|
|
**Market trend analysis with price insights**
|
|
- **Description**: Analyze price trends and market data for an address
|
|
- **Parameters**:
|
|
- `address` (required): The address to analyze
|
|
- `years_back` (optional): Number of years to analyze (default: 2)
|
|
- **Returns**: Market analysis with trends, average prices, and insights
|
|
|
|
**Example usage:**
|
|
```json
|
|
{
|
|
"address": "דיזנגוף 50 תל אביב",
|
|
"years_back": 5
|
|
}
|
|
```
|
|
|
|
##### 🏘️ `compare_neighborhoods`
|
|
**Compare multiple areas**
|
|
- **Description**: Compare real estate data across multiple addresses or neighborhoods
|
|
- **Parameters**:
|
|
- `addresses` (required): List of addresses to compare
|
|
- `years_back` (optional): Number of years to analyze (default: 2)
|
|
- **Returns**: Comparative analysis with rankings and insights
|
|
|
|
**Example usage:**
|
|
```json
|
|
{
|
|
"addresses": ["סוקולוב 38 חולון", "בן יהודה 1 תל אביב", "דיזנגוף 50 תל אביב"],
|
|
"years_back": 2
|
|
}
|
|
```
|
|
|
|
##### 🔍 `autocomplete_address`
|
|
**Address search and validation**
|
|
- **Description**: Search for and validate Israeli addresses
|
|
- **Parameters**:
|
|
- `search_text` (required): The address text to search for
|
|
- **Returns**: List of matching addresses with coordinates
|
|
|
|
**Example usage:**
|
|
```json
|
|
{
|
|
"search_text": "רוטשילד תל אביב"
|
|
}
|
|
```
|
|
|
|
#### Server Features
|
|
|
|
- **Async Operations**: All tools run asynchronously for better performance
|
|
- **Error Handling**: Comprehensive error handling with meaningful error messages
|
|
- **Logging**: Detailed logging for debugging and monitoring
|
|
- **Data Validation**: Input validation and sanitization
|
|
- **Hebrew Support**: Full support for Hebrew addresses and text
|
|
|
|
#### Testing the Server
|
|
|
|
You can test the server using the interactive demo:
|
|
|
|
```bash
|
|
python simple_mcp_server.py
|
|
```
|
|
|
|
This will start an interactive session where you can:
|
|
1. List available tools
|
|
2. Call tools with parameters
|
|
3. See formatted results
|
|
4. Test error handling
|
|
|
|
#### Server Logs
|
|
|
|
The server provides detailed logging. To see debug information:
|
|
|
|
```bash
|
|
# Set logging level before running
|
|
export PYTHONPATH=/path/to/nadlan-mcp
|
|
python -c "import logging; logging.basicConfig(level=logging.DEBUG)" run_mcp_server.py
|
|
```
|
|
|
|
#### Troubleshooting
|
|
|
|
**Connection Issues:**
|
|
- Ensure all dependencies are installed: `pip install -r requirements.txt`
|
|
- Check that Python path is correct in client configuration
|
|
- Verify the server starts without errors
|
|
|
|
**Tool Execution Issues:**
|
|
- Check network connectivity for API calls
|
|
- Verify address format (Hebrew addresses work best)
|
|
- Review server logs for detailed error information
|
|
|
|
**Performance:**
|
|
- Use appropriate `years_back` values (2-5 years recommended)
|
|
- Large radius searches may take longer
|
|
- Consider caching results for repeated queries
|
|
|
|
### Python Library Usage
|
|
|
|
```python
|
|
from nadlan_mcp import GovmapClient
|
|
|
|
# Initialize the client
|
|
client = GovmapClient()
|
|
|
|
# Search for recent deals for a specific address
|
|
address = "סוקולוב 38 חולון"
|
|
deals = client.find_recent_deals_for_address(address, years_back=2)
|
|
|
|
print(f"Found {len(deals)} deals for {address}")
|
|
for deal in deals[:5]: # Show first 5 deals
|
|
print(f"Address: {deal.get('address')}")
|
|
print(f"Date: {deal.get('dealDate')}")
|
|
print(f"Price: {deal.get('price')}")
|
|
print("---")
|
|
```
|
|
|
|
### Advanced Usage Examples
|
|
|
|
#### 1. Address Autocomplete
|
|
|
|
```python
|
|
from nadlan_mcp import GovmapClient
|
|
|
|
client = GovmapClient()
|
|
|
|
# Search for an address
|
|
result = client.autocomplete_address("בן יהודה 1 תל אביב")
|
|
if result['results']:
|
|
best_match = result['results'][0]
|
|
print(f"Found: {best_match.get('displayName')}")
|
|
print(f"Coordinates: {best_match.get('point')}")
|
|
```
|
|
|
|
#### 2. Get Block and Parcel Information
|
|
|
|
```python
|
|
# Get coordinates from address first
|
|
autocomplete_result = client.autocomplete_address("דיזנגוף 50 תל אביב")
|
|
point = tuple(autocomplete_result['results'][0]['point'])
|
|
|
|
# Get block and parcel info
|
|
gush_helka = client.get_gush_helka(point)
|
|
print(f"Block/Parcel info: {gush_helka}")
|
|
```
|
|
|
|
#### 3. Find Deals by Radius
|
|
|
|
```python
|
|
# Find deals within 100 meters of a point
|
|
point = (3870923.95, 3766288.07) # Example coordinates
|
|
deals = client.get_deals_by_radius(point, radius=100)
|
|
|
|
print(f"Found {len(deals)} deals within 100m")
|
|
for deal in deals:
|
|
print(f"- {deal.get('address')}: {deal.get('price')}")
|
|
```
|
|
|
|
#### 4. Street-specific Deals
|
|
|
|
```python
|
|
# Get detailed street deals for a specific polygon
|
|
polygon_id = "52190246"
|
|
street_deals = client.get_street_deals(
|
|
polygon_id,
|
|
limit=10,
|
|
start_date="2023-01",
|
|
end_date="2024-01"
|
|
)
|
|
|
|
print(f"Found {len(street_deals)} street deals")
|
|
```
|
|
|
|
#### 5. Neighborhood Analysis
|
|
|
|
```python
|
|
# Get neighborhood deals
|
|
neighborhood_deals = client.get_neighborhood_deals(
|
|
polygon_id="52282030",
|
|
limit=20,
|
|
start_date="2023-01",
|
|
end_date="2024-01"
|
|
)
|
|
|
|
print(f"Found {len(neighborhood_deals)} neighborhood deals")
|
|
```
|
|
|
|
### Running the Example Script
|
|
|
|
The project includes a main example script that demonstrates basic usage:
|
|
|
|
```bash
|
|
python -m nadlan_mcp.main
|
|
```
|
|
|
|
Or run it directly:
|
|
|
|
```bash
|
|
python nadlan_mcp/main.py
|
|
```
|
|
|
|
## API Reference
|
|
|
|
### GovmapClient Class
|
|
|
|
The main class for interacting with the Govmap API.
|
|
|
|
#### Methods
|
|
|
|
##### `__init__(base_url: str = "https://www.govmap.gov.il/api/")`
|
|
Initialize the client with the base API URL.
|
|
|
|
##### `autocomplete_address(search_text: str) -> Dict[str, Any]`
|
|
Search for addresses using autocomplete functionality.
|
|
|
|
- **Parameters:**
|
|
- `search_text`: The address to search for (Hebrew or English)
|
|
- **Returns:** Dictionary with search results and coordinates
|
|
- **Raises:** `requests.RequestException`, `ValueError`
|
|
|
|
##### `get_gush_helka(point: Tuple[float, float]) -> Dict[str, Any]`
|
|
Get block (Gush) and parcel (Helka) information for coordinates.
|
|
|
|
- **Parameters:**
|
|
- `point`: Tuple of (longitude, latitude)
|
|
- **Returns:** Dictionary with block and parcel data
|
|
- **Raises:** `requests.RequestException`, `ValueError`
|
|
|
|
##### `get_deals_by_radius(point: Tuple[float, float], radius: int = 50) -> List[Dict[str, Any]]`
|
|
Find deals within a specified radius of a point.
|
|
|
|
- **Parameters:**
|
|
- `point`: Tuple of (longitude, latitude)
|
|
- `radius`: Search radius in meters (default: 50)
|
|
- **Returns:** List of deal dictionaries
|
|
- **Raises:** `requests.RequestException`
|
|
|
|
##### `get_street_deals(polygon_id: str, limit: int = 10, start_date: Optional[str] = None, end_date: Optional[str] = None) -> List[Dict[str, Any]]`
|
|
Get detailed deals for a specific street.
|
|
|
|
- **Parameters:**
|
|
- `polygon_id`: The polygon ID for the street
|
|
- `limit`: Maximum number of deals to return (default: 10)
|
|
- `start_date`: Start date in 'YYYY-MM' format
|
|
- `end_date`: End date in 'YYYY-MM' format
|
|
- **Returns:** List of detailed deal information
|
|
- **Raises:** `requests.RequestException`
|
|
|
|
##### `get_neighborhood_deals(polygon_id: str, limit: int = 10, start_date: Optional[str] = None, end_date: Optional[str] = None) -> List[Dict[str, Any]]`
|
|
Get deals within the same neighborhood.
|
|
|
|
- **Parameters:**
|
|
- `polygon_id`: The polygon ID for the area
|
|
- `limit`: Maximum number of deals to return (default: 10)
|
|
- `start_date`: Start date in 'YYYY-MM' format
|
|
- `end_date`: End date in 'YYYY-MM' format
|
|
- **Returns:** List of neighborhood deals
|
|
- **Raises:** `requests.RequestException`
|
|
|
|
##### `find_recent_deals_for_address(address: str, years_back: int = 2) -> List[Dict[str, Any]]`
|
|
**Main function**: Find all relevant deals for an address (combines all other methods).
|
|
|
|
- **Parameters:**
|
|
- `address`: The address to search for
|
|
- `years_back`: How many years back to search (default: 2)
|
|
- **Returns:** List of all relevant deals, sorted by date
|
|
- **Raises:** `ValueError`, `requests.RequestException`
|
|
|
|
## Govmap API Endpoints
|
|
|
|
This project uses the following Govmap API endpoints:
|
|
|
|
- **Autocomplete**: `POST /search-service/autocomplete`
|
|
- **Entities by Point**: `POST /layers-catalog/entitiesByPoint`
|
|
- **Deals by Radius**: `GET /real-estate/deals/{point}/{radius}`
|
|
- **Street Deals**: `GET /real-estate/street-deals/{polygon_id}`
|
|
- **Neighborhood Deals**: `GET /real-estate/neighborhood-deals/{polygon_id}`
|
|
|
|
### API Base URL
|
|
```
|
|
https://www.govmap.gov.il/api/
|
|
```
|
|
|
|
## Error Handling
|
|
|
|
The client includes comprehensive error handling:
|
|
|
|
- **Network Errors**: Handles connection issues and API timeouts
|
|
- **API Errors**: Manages HTTP error responses and invalid data
|
|
- **Data Validation**: Validates API responses and handles missing data
|
|
- **Logging**: Provides detailed logging for debugging issues
|
|
|
|
## Logging
|
|
|
|
The project uses Python's built-in logging module. To enable debug logging:
|
|
|
|
```python
|
|
import logging
|
|
logging.basicConfig(level=logging.DEBUG)
|
|
```
|
|
|
|
## Dependencies
|
|
|
|
- **requests**: HTTP library for API calls
|
|
- **python-dotenv**: Environment variable management
|
|
- **mcp**: Model Context Protocol SDK for AI agent integration
|
|
- **pytest**: Testing framework
|
|
|
|
## License
|
|
|
|
This project is licensed under the MIT License - see the LICENSE file for details.
|
|
|
|
## Contributing
|
|
|
|
1. Fork the repository
|
|
2. Create a feature branch
|
|
3. Make your changes
|
|
4. Add tests if applicable
|
|
5. Submit a pull request
|
|
|
|
## Disclaimer
|
|
|
|
This tool is for educational and professional use only. Please respect the Govmap API terms of service and rate limits. The authors are not responsible for any misuse of this tool.
|
|
|
|
## Support
|
|
|
|
For issues, questions, or contributions, please create an issue in the repository.
|
|
|
|
---
|
|
|
|
**Note**: This project is not officially affiliated with the Israeli government or Govmap. It is an independent tool created to facilitate access to public real estate data.
|