Python-based MCP server for querying Israeli government public real estate data via the Govmap API. Provides comprehensive property deal analysis including address autocomplete, geospatial block/parcel (gush/helka) lookup, recent transaction discovery by radius, street-level and neighborhood-level deal aggregation, market trend analysis with price insights, and multi-address comparison. Supports Hebrew addresses natively and returns deal prices, dates, and property details from official government records.
Those looking to buy or rent an apartment in Israel struggle to access real estate transaction data. The information exists in GovMap but the interface is cumbersome and does not easily allow trend analysis, neighborhood comparison, or radius-based deal search.
Clone from GitHub to install
git clone https://github.com/nitzpo/nadlan-mcp
cd nadlan-mcp
pip install -r requirements.txt.mcp.json
{
"mcpServers": {
"nadlan": {
"command": "python",
"args": [
"run_fastmcp_server.py"
],
"cwd": "/path/to/nadlan-mcp"
}
}
}Find recent real estate deals within a kilometer radius of 50 Dizengoff Street, Tel Aviv
Compare apartment prices between the Rechavia and Baka neighborhoods in Jerusalem
Show me the apartment price trend on Rothschild Boulevard in Tel Aviv over the last two years
What are the recent prices at Dizengoff 50, Tel Aviv?
Compare apartment prices between Ramat Gan and Givatayim
What is the price trend in the Rechavia neighborhood in Jerusalem?
Show recent real estate deals near Herzliya Pituach
Analyze the real estate market in Netanya over the last 3 years
MCP server providing programmatic access to Israeli Land Authority (ILA/Rami) public tender data. Offers comprehensive search and filtering of government land tenders by type, location, status, and dates, with full Hebrew Unicode support. Features active tender listings, detailed tender information, geographic mapping data, recent tender outcomes, and settlement code lookups. Also exposes static reference data resources for tender types, regions, land uses, statuses, and priority populations.
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