Files
nadlan-mcp/nadlan_mcp
Nitzan Pomerantz 247ddad8cd CRITICAL FIX: get_deals_by_radius returns polygon metadata, not deals
## Root Cause
After Pydantic migration, get_deals_by_radius() was attempting to validate
API responses as Deal objects. However, this endpoint returns POLYGON METADATA
(with fields: dealscount, polygon_id, settlementNameHeb), NOT individual deals.

All responses failed Pydantic validation (missing dealAmount, dealDate),
resulting in empty lists and 0 deals returned from ALL queries.

## Fixes Applied

### 1. client.py - get_deals_by_radius()
- Return type: `List[Deal]` → `List[Dict[str, Any]]`
- Remove Pydantic validation - return raw metadata dicts
- Update docstring to clarify this returns polygon metadata
- Add note to use find_recent_deals_for_address() for actual deals

### 2. client.py - find_recent_deals_for_address()
- Update to handle polygon metadata dicts (not Deal objects)
- Use dict.get('polygon_id') instead of model attribute access
- Rename variable: `nearby_deals` → `nearby_polygons` for clarity

### 3. fastmcp_server.py - get_deals_by_radius() tool
- Update to handle dict responses (not Deal objects)
- Remove strip_bloat_fields() call (not needed for metadata)
- Update docstring with WARNING about polygon metadata
- Change response keys: "deals" → "polygons", "total_deals" → "total_polygons"

### 4. Tests
- test_govmap_client.py: Update to expect dicts, not Deal objects
- test_fastmcp_tools.py: Update 3 tests to mock dict responses

## Impact
-  find_recent_deals_for_address() NOW WORKS (was returning 0 deals)
-  All 174 tests passing
-  E2E API test confirmed working with real data

## API Behavior Documented
get_deals_by_radius endpoint design:
1. Returns polygon/area metadata (not individual deals)
2. Extract polygon_ids from metadata
3. Call get_street_deals(polygon_id) to get actual deals
4. This workflow is automated in find_recent_deals_for_address()

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-27 09:38:21 +02:00
..
2025-10-26 10:58:46 +02:00
2025-10-19 00:58:46 +03:00
2025-07-13 01:03:15 +03:00