Testing update

2025-10-27 23:33:09 +02:00
parent 247ddad8cd
commit a234e809bf
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+# Testing Strategy
+
+## Overview
+
+Nadlan-MCP uses a three-tier testing approach:
+1. **Fast unit tests** - Cached fixtures, run in <1s (default)
+2. **E2E smoke tests** - Minimal API calls, run in ~5s (verify API works)
+3. **Comprehensive E2E tests** - Full API coverage, run in ~5min (optional)
+
+## Running Tests
+
+### Default: Fast Unit Tests Only
+```bash
+pytest tests/ --ignore=tests/e2e/
+# Result: 180 passed, 1 skipped in 0.39s
+```
+
+### E2E Smoke Tests (Fast)
+```bash
+pytest tests/e2e/test_mcp_tools.py -m integration
+# Result: 4 passed in 4.77s
+```
+
+### Comprehensive E2E Tests (Slow - Optional)
+```bash
+pytest tests/e2e/test_mcp_tools_comprehensive.py -m integration
+# Result: 11 passed in 5m36s
+```
+
+### All Tests
+```bash
+pytest tests/
+```
+
+## Test Structure
+
+### Fast Unit Tests (`tests/`)
+- **174 tests** covering all core functionality
+- Use cached API responses from `tests/fixtures/`
+- Mock `GovmapClient` to avoid real API calls
+- Run in **0.39 seconds**
+
+Key test files:
+- `tests/govmap/test_models.py` - Pydantic model validation (36 tests)
+- `tests/govmap/test_utils.py` - Helper functions (45 tests)
+- `tests/govmap/test_validators.py` - Input validation (24 tests)
+- `tests/test_govmap_client.py` - Client and business logic (41 tests)
+- `tests/test_fastmcp_tools.py` - MCP tool integration (22 tests)
+- `tests/test_mcp_tools_fast.py` - Fast MCP tool tests with fixtures (6 tests)
+
+### E2E Smoke Tests (`tests/e2e/test_mcp_tools.py`)
+- **4 minimal smoke tests** with real API calls
+- Verify API connectivity and basic functionality
+- Use minimal data (small limits, small radius)
+- Run in **4.77 seconds**
+
+### Comprehensive E2E Tests (`tests/e2e/test_mcp_tools_comprehensive.py`)
+- **11 thorough integration tests** with real API calls
+- Test all 10 MCP tools with full data
+- Verify complete workflow from MCP tool → API → response
+- Catch API contract changes
+- Run in **5min 36sec** (optional, use for releases)
+
+## Fixtures
+
+Cached API responses in `tests/fixtures/`:
+- `autocomplete_response.json` - Address search results
+- `street_deals.json` - Street-level deal data
+- `neighborhood_deals.json` - Neighborhood-level deal data
+- `polygon_metadata.json` - Polygon metadata from radius search
+
+These fixtures are generated from real API calls and updated as needed.
+
+## Test Markers
+
+Configured in `pytest.ini`:
+- `@pytest.mark.integration` - Slow tests requiring real API calls
+- `@pytest.mark.unit` - Fast unit tests (default)
+
+## Performance Comparison
+
+| Test Suite | Count | Duration | Speed |
+|------------|-------|----------|-------|
+| Fast unit tests | 180 | 0.39s | 462 tests/sec |
+| E2E smoke tests | 4 | 4.77s | 0.84 tests/sec |
+| Comprehensive E2E | 11 | 5m36s | 0.033 tests/sec |
+
+**Unit tests are 12x faster than smoke tests, 860x faster than comprehensive E2E!**
+
+## CI/CD Recommendations
+
+### PR Checks (~5s)
+```bash
+# Run unit tests + smoke tests
+pytest tests/ --ignore=tests/e2e/test_mcp_tools_comprehensive.py
+```
+
+### Nightly Build (~6min)
+```bash
+# Run all tests including comprehensive E2E
+pytest tests/
+```
+
+### Quick Verification (<5s)
+```bash
+# Just smoke tests to verify API works
+pytest tests/e2e/test_mcp_tools.py -m integration
+```
+
+## Updating Fixtures
+
+When API responses change, regenerate fixtures:
+
+```bash
+source venv/bin/activate
+python << 'EOF'
+import json
+from nadlan_mcp.govmap import GovmapClient
+
+client = GovmapClient()
+
+# Update autocomplete fixture
+autocomplete_response = client.autocomplete_address("חולון סוקולוב")
+with open("tests/fixtures/autocomplete_response.json", "w", encoding="utf-8") as f:
+    json.dump([r.model_dump() for r in autocomplete_response.results], f, ensure_ascii=False, indent=2)
+
+# Update street deals
+street_deals = client.get_street_deals("52385050", limit=10)
+with open("tests/fixtures/street_deals.json", "w", encoding="utf-8") as f:
+    json.dump([d.model_dump(mode='json') for d in street_deals], f, ensure_ascii=False, indent=2)
+
+# Update neighborhood deals
+neighborhood_deals = client.get_neighborhood_deals("52385050", limit=10)
+with open("tests/fixtures/neighborhood_deals.json", "w", encoding="utf-8") as f:
+    json.dump([d.model_dump(mode='json') for d in neighborhood_deals], f, ensure_ascii=False, indent=2)
+
+# Update polygon metadata
+polygons = client.get_deals_by_radius((3870928.84, 3766290.19), radius=500)
+with open("tests/fixtures/polygon_metadata.json", "w", encoding="utf-8") as f:
+    json.dump(polygons[:10], f, ensure_ascii=False, indent=2)
+
+print("✓ Fixtures updated")
+EOF
+```
+
+## Test Coverage
+
+Run with coverage reporting:
+```bash
+pytest --cov=nadlan_mcp --cov-report=html
+open htmlcov/index.html
+```
@@ -0,0 +1 @@
+"""End-to-end tests for MCP tools."""
@@ -0,0 +1,72 @@
+"""
+Fast E2E smoke tests for MCP tools (<30 seconds).
+
+These tests make MINIMAL real API calls to verify the service is working.
+For comprehensive E2E testing, see test_mcp_tools_comprehensive.py
+
+Target: Complete in <30 seconds
+"""
+import json
+import pytest
+from nadlan_mcp.fastmcp_server import (
+    autocomplete_address,
+    find_recent_deals_for_address,
+    get_street_deals,
+    get_deals_by_radius,
+)
+
+
+@pytest.mark.integration
+class TestMCPToolsSmokeTests:
+    """Minimal E2E smoke tests to verify API connectivity."""
+
+    # Known working data
+    TEST_ADDRESS = "סוקולוב 38 חולון"
+    TEST_POLYGON_ID = "52385050"
+    TEST_LAT = 3766290.19
+    TEST_LON = 3870928.84
+
+    def test_autocomplete_works(self):
+        """Smoke test: Autocomplete returns results."""
+        result = autocomplete_address("חולון")
+        data = json.loads(result)
+
+        assert isinstance(data, list)
+        assert len(data) > 0
+        assert "text" in data[0]
+
+    def test_get_street_deals_works(self):
+        """Smoke test: Can fetch street deals."""
+        # Use small limit for speed
+        result = get_street_deals(self.TEST_POLYGON_ID, limit=5, deal_type=2)
+        data = json.loads(result)
+
+        assert "total_deals" in data
+        assert data["total_deals"] > 0
+        assert "deals" in data
+
+    def test_get_deals_by_radius_works(self):
+        """Smoke test: Can fetch polygon metadata by radius."""
+        # Use small radius for speed
+        result = get_deals_by_radius(self.TEST_LAT, self.TEST_LON, radius_meters=100)
+        data = json.loads(result)
+
+        assert "total_polygons" in data
+        assert data["total_polygons"] > 0
+
+    def test_find_recent_deals_minimal(self):
+        """Smoke test: Main tool works with minimal data."""
+        # Use very small limits to speed up
+        result = find_recent_deals_for_address(
+            self.TEST_ADDRESS,
+            years_back=1,
+            radius_meters=30,
+            max_deals=10
+        )
+        data = json.loads(result)
+
+        # Just verify structure, don't check counts
+        assert "search_parameters" in data
+        assert "market_statistics" in data
+        assert "deals" in data
+        assert isinstance(data["deals"], list)
@@ -0,0 +1,185 @@
+"""
+End-to-end tests for all MCP tools.
+
+These tests make real API calls to verify the complete functionality
+of each MCP tool from end to end.
+
+Mark as integration tests since they hit real APIs.
+"""
+import json
+import pytest
+from nadlan_mcp.fastmcp_server import (
+    autocomplete_address,
+    find_recent_deals_for_address,
+    analyze_market_trends,
+    get_valuation_comparables,
+    get_deal_statistics,
+    get_market_activity_metrics,
+    compare_addresses,
+    get_street_deals,
+    get_neighborhood_deals,
+    get_deals_by_radius,
+)
+
+
+@pytest.mark.integration
+class TestMCPToolsE2E:
+    """End-to-end tests for all 10 MCP tools."""
+
+    # Test addresses
+    TEST_ADDRESS_1 = "סוקולוב 38 חולון"
+    TEST_ADDRESS_2 = "דיזנגוף 50 תל אביב"
+    TEST_POLYGON_ID = "52385050"  # Known polygon with data
+    # ITM coordinates for Holon (lat, lon format for MCP tool)
+    TEST_LAT = 3766290.19
+    TEST_LON = 3870928.84
+
+    def test_autocomplete_address(self):
+        """Test address autocomplete returns results."""
+        result = autocomplete_address("חולון סוקולוב")
+        data = json.loads(result)
+
+        assert isinstance(data, list)
+        assert len(data) > 0
+
+        # Check first result has expected structure
+        first = data[0]
+        assert "text" in first
+        assert "coordinates" in first or "id" in first
+
+    def test_find_recent_deals_for_address(self):
+        """Test finding recent deals for an address."""
+        result = find_recent_deals_for_address(self.TEST_ADDRESS_1, max_deals=100)
+        data = json.loads(result)
+
+        # Check response structure
+        assert "search_parameters" in data
+        assert "market_statistics" in data
+        assert "deals" in data
+
+        # Verify some deals were found
+        assert isinstance(data["deals"], list)
+        assert len(data["deals"]) > 0
+
+        # Check deal structure
+        deal = data["deals"][0]
+        assert "deal_amount" in deal
+        assert "deal_date" in deal
+        assert "settlement_name_heb" in deal
+
+    def test_analyze_market_trends(self):
+        """Test market trend analysis."""
+        result = analyze_market_trends(
+            self.TEST_ADDRESS_1, years_back=3, radius_meters=100
+        )
+        data = json.loads(result)
+
+        # Check response structure
+        assert "market_summary" in data
+        assert "total_deals" in data["market_summary"]
+        assert isinstance(data["market_summary"]["total_deals"], int)
+        assert data["market_summary"]["total_deals"] >= 0
+
+    def test_get_valuation_comparables(self):
+        """Test getting valuation comparables."""
+        result = get_valuation_comparables(
+            self.TEST_ADDRESS_1,
+            years_back=3,
+            min_rooms=3.0,
+            max_rooms=5.0
+        )
+        data = json.loads(result)
+
+        assert "total_comparables" in data
+        assert isinstance(data["total_comparables"], int)
+        assert data["total_comparables"] >= 0
+
+        if data["total_comparables"] > 0:
+            assert "comparables" in data
+            comp = data["comparables"][0]
+            assert "deal_amount" in comp
+            assert "asset_room_num" in comp
+
+    def test_get_deal_statistics(self):
+        """Test deal statistics calculation."""
+        result = get_deal_statistics(self.TEST_ADDRESS_1, years_back=3)
+        data = json.loads(result)
+
+        # Check response structure
+        assert "statistics" in data
+        if "sample_size" in data["statistics"]:
+            assert isinstance(data["statistics"]["sample_size"], int)
+            assert data["statistics"]["sample_size"] >= 0
+
+    def test_get_market_activity_metrics(self):
+        """Test market activity metrics."""
+        result = get_market_activity_metrics(self.TEST_ADDRESS_1, years_back=3)
+        data = json.loads(result)
+
+        # Check response structure
+        assert "market_activity" in data
+        if data["market_activity"] is not None:
+            assert "activity_score" in data["market_activity"]
+
+    def test_compare_addresses(self):
+        """Test comparing multiple addresses."""
+        result = compare_addresses([self.TEST_ADDRESS_1, self.TEST_ADDRESS_2])
+        data = json.loads(result)
+
+        assert isinstance(data, dict)
+        assert "addresses_compared" in data
+        assert "all_results" in data
+
+    def test_get_street_deals(self):
+        """Test getting street-level deals."""
+        result = get_street_deals(self.TEST_POLYGON_ID, limit=100, deal_type=2)
+        data = json.loads(result)
+
+        assert "total_deals" in data
+        assert isinstance(data["total_deals"], int)
+        assert data["total_deals"] > 0  # Known polygon should have deals
+
+        assert "deals" in data
+        assert len(data["deals"]) > 0
+
+        # Check deal structure
+        deal = data["deals"][0]
+        assert "deal_amount" in deal
+        assert "deal_date" in deal
+
+    def test_get_neighborhood_deals(self):
+        """Test getting neighborhood-level deals."""
+        result = get_neighborhood_deals(self.TEST_POLYGON_ID, limit=100, deal_type=2)
+        data = json.loads(result)
+
+        assert "total_deals" in data
+        assert isinstance(data["total_deals"], int)
+        assert data["total_deals"] > 0  # Known polygon should have deals
+
+        assert "deals" in data
+        assert len(data["deals"]) > 0
+
+    def test_get_deals_by_radius(self):
+        """Test getting polygon metadata by radius."""
+        result = get_deals_by_radius(self.TEST_LAT, self.TEST_LON, radius_meters=500)
+        data = json.loads(result)
+
+        assert "total_polygons" in data
+        assert isinstance(data["total_polygons"], int)
+        assert data["total_polygons"] > 0  # Known coords should have polygons
+
+        assert "polygons" in data
+        assert len(data["polygons"]) > 0
+
+        # Check polygon metadata structure
+        polygon = data["polygons"][0]
+        assert "polygon_id" in polygon or "objectid" in polygon
+
+    def test_get_deals_by_radius_no_results(self):
+        """Test get_deals_by_radius with coords that have no data."""
+        # Use coordinates unlikely to have data
+        result = get_deals_by_radius(37.66, 38.71, radius_meters=10)
+
+        # Should return a message string, not JSON
+        assert isinstance(result, str)
+        assert "No polygons found" in result or "total_polygons" in result
@@ -0,0 +1,35 @@
+[
+  {
+    "text": "סוקולוב חולון",
+    "id": "street|STREET_MID_POINT|40087",
+    "type": "street",
+    "score": 1658.0989,
+    "coordinates": {
+      "longitude": 3871467.9873431968,
+      "latitude": 3766276.9742487124
+    },
+    "shape": "POINT(3871467.9873431968 3766276.9742487124)"
+  },
+  {
+    "text": "קופת חולים - לאומית סוקולוב חולון",
+    "id": "institutes|POI_BLDG|71871",
+    "type": "institutes",
+    "score": 1095.5675,
+    "coordinates": {
+      "longitude": 3871143.6159368134,
+      "latitude": 3766329.3192062005
+    },
+    "shape": "POINT(3871143.6159368134 3766329.3192062005)"
+  },
+  {
+    "text": "קופת חולים - לאומית סוקולוב חולון",
+    "id": "poi|POI_MID_POINT|102233",
+    "type": "poi",
+    "score": 1099.5448,
+    "coordinates": {
+      "longitude": 3871143.6159681133,
+      "latitude": 3766329.319199102
+    },
+    "shape": "POINT(3871143.6159681133 3766329.319199102)"
+  }
+]
@@ -0,0 +1,332 @@
+[
+  {
+    "objectid": 1969420,
+    "deal_amount": 1600000.0,
+    "deal_date": "2025-09-11",
+    "asset_area": 61.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3870720.4640780594 3766261.471274853,3870704.822454856 3766280.494942658,3870715.8743646624 3766289.5618421077,3870731.3745853226 3766270.5375762666,3870720.4640780594 3766261.471274853)))",
+    "source_polygon_id": null,
+    "sourceorder": null,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000721,
+    "streetNameHeb": "בילינסון",
+    "streetNameEng": "Belinson",
+    "houseNum": 6,
+    "floorNo": "רביעית",
+    "dealId": 3633677206,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 3,
+    "gushNum": 7172,
+    "parcelNum": 235,
+    "subParcelNum": 11,
+    "polygonId": "52995209",
+    "price_per_sqm": 26229.51
+  },
+  {
+    "objectid": 1968034,
+    "deal_amount": 1800000.0,
+    "deal_date": "2025-08-21",
+    "asset_area": 51.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3871546.267254118 3766046.2332329005,3871519.7450213963 3766048.8632871644,3871520.755660357 3766058.564386736,3871529.006896269 3766057.780093892,3871529.5742626246 3766063.3353820755,3871547.727459817 3766061.4891484776,3871546.267254118 3766046.2332329005)))",
+    "source_polygon_id": null,
+    "sourceorder": null,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000415,
+    "streetNameHeb": "חנקין",
+    "streetNameEng": "Hankin",
+    "houseNum": 62,
+    "floorNo": "שניה",
+    "dealId": 3632991008,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 3,
+    "gushNum": 7170,
+    "parcelNum": 91,
+    "subParcelNum": 8,
+    "polygonId": "52487416",
+    "price_per_sqm": 35294.12
+  },
+  {
+    "objectid": 1972678,
+    "deal_amount": 2170000.0,
+    "deal_date": "2025-08-20",
+    "asset_area": 90.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3870461.085939886 3765412.661079392,3870461.8556948095 3765419.4469509623,3870454.5119660264 3765416.0582189877,3870449.8311605644 3765416.7315218183,3870448.8832249534 3765412.6281236825,3870444.1110105794 3765413.266600847,3870448.3403304657 3765432.7404882894,3870508.9368100218 3765424.106078474,3870506.5193002103 3765406.631910944,3870482.4682015995 3765409.8236224824,3870476.137660146 3765410.663707863,3870461.085939886 3765412.661079392)))",
+    "source_polygon_id": null,
+    "sourceorder": null,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000720,
+    "streetNameHeb": "לאון בלום",
+    "streetNameEng": "L?on Blum",
+    "houseNum": 64,
+    "floorNo": "שניה",
+    "dealId": 3633156134,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 4,
+    "gushNum": 7176,
+    "parcelNum": 9,
+    "subParcelNum": 59,
+    "polygonId": "52202717",
+    "price_per_sqm": 24111.11
+  },
+  {
+    "objectid": 1967412,
+    "deal_amount": 2050000.0,
+    "deal_date": "2025-08-14",
+    "asset_area": 95.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3871347.8555616946 3766162.0722470563,3871334.99564493 3766163.205144352,3871336.9037298146 3766187.3432294633,3871349.869159977 3766186.35283101,3871347.8555616946 3766162.0722470563)))",
+    "source_polygon_id": null,
+    "sourceorder": null,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000443,
+    "streetNameHeb": "שפרינצק",
+    "streetNameEng": "Sprinzak",
+    "houseNum": 29,
+    "floorNo": "שניה",
+    "dealId": 3632926686,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 4,
+    "gushNum": 7170,
+    "parcelNum": 28,
+    "subParcelNum": 6,
+    "polygonId": "53339618",
+    "price_per_sqm": 21578.95
+  },
+  {
+    "objectid": 1972438,
+    "deal_amount": 2057000.0,
+    "deal_date": "2025-08-13",
+    "asset_area": 70.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3870628.707375865 3765928.3916899217,3870616.197248105 3765933.4442600156,3870624.479632951 3765954.33986368,3870628.9524073373 3765952.58190368,3870629.4304386983 3765953.8507194677,3870634.044605639 3765952.0933281765,3870632.98273369 3765949.4960702136,3870635.237077585 3765948.5461212373,3870632.1913898066 3765941.121957529,3870633.501643529 3765940.5352417007,3870628.707375865 3765928.3916899217)))",
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+  {
+    "objectid": 1960643,
+    "deal_amount": 100000.0,
+    "deal_date": "2008-11-09",
+    "asset_area": 58.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3870903.639498367 3766273.3642689525,3870887.6103521264 3766277.301987773,3870893.7433254845 3766302.5584789426,3870909.784521754 3766298.561590301,3870903.639498367 3766273.3642689525)))",
+    "source_polygon_id": null,
+    "sourceorder": 1,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000401,
+    "streetNameHeb": "סוקולוב",
+    "streetNameEng": "Sokolov",
+    "houseNum": 32,
+    "floorNo": "שלישית",
+    "dealId": 3139951568,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 3,
+    "gushNum": 7166,
+    "parcelNum": 141,
+    "subParcelNum": 12,
+    "polygonId": "52385050",
+    "price_per_sqm": 1724.14
+  },
+  {
+    "objectid": 1960647,
+    "deal_amount": 430000.0,
+    "deal_date": "2008-06-17",
+    "asset_area": 42.0,
+    "settlement_name_heb": "חולון",
+    "property_type_description": "דירה",
+    "neighborhood": "קרית עבודה",
+    "street_name": null,
+    "house_number": null,
+    "floor": null,
+    "floor_number": null,
+    "rooms": null,
+    "priority": null,
+    "shape": "MULTIPOLYGON(((3870903.639498367 3766273.3642689525,3870887.6103521264 3766277.301987773,3870893.7433254845 3766302.5584789426,3870909.784521754 3766298.561590301,3870903.639498367 3766273.3642689525)))",
+    "source_polygon_id": null,
+    "sourceorder": 1,
+    "settlementId": 6600,
+    "settlementNameEng": "Holon",
+    "streetCode": 66000401,
+    "streetNameHeb": "סוקולוב",
+    "streetNameEng": "Sokolov",
+    "houseNum": 32,
+    "floorNo": "שניה",
+    "dealId": 3137311234,
+    "dealNatureDescription": "דירה בבית קומות",
+    "assetRoomNum": 2,
+    "gushNum": 7166,
+    "parcelNum": 141,
+    "subParcelNum": 9,
+    "polygonId": "52385050",
+    "price_per_sqm": 10238.1
+  }
+]
@@ -0,0 +1,155 @@
+"""
+Fast unit tests for MCP tools using cached fixtures.
+
+These tests use pre-recorded API responses to run quickly (~1s)
+without hitting the real Govmap API.
+
+For full E2E tests with real API calls, see tests/e2e/test_mcp_tools.py
+"""
+import json
+import pytest
+from pathlib import Path
+from unittest.mock import patch, Mock
+from nadlan_mcp.govmap.models import Deal, AutocompleteResult, AutocompleteResponse, CoordinatePoint
+from nadlan_mcp.fastmcp_server import (
+    autocomplete_address,
+    find_recent_deals_for_address,
+    get_street_deals,
+    get_neighborhood_deals,
+    get_deals_by_radius,
+)
+
+
+# Load fixtures
+FIXTURES_DIR = Path(__file__).parent / "fixtures"
+
+
+def load_fixture(filename):
+    """Load a JSON fixture file."""
+    with open(FIXTURES_DIR / filename, encoding="utf-8") as f:
+        return json.load(f)
+
+
+@pytest.fixture
+def mock_autocomplete_data():
+    """Cached autocomplete response."""
+    data = load_fixture("autocomplete_response.json")
+    results = [AutocompleteResult.model_validate(r) for r in data]
+    return AutocompleteResponse(results=results, resultsCount=len(results))
+
+
+@pytest.fixture
+def mock_street_deals_data():
+    """Cached street deals response."""
+    data = load_fixture("street_deals.json")
+    return [Deal.model_validate(d) for d in data]
+
+
+@pytest.fixture
+def mock_neighborhood_deals_data():
+    """Cached neighborhood deals response."""
+    data = load_fixture("neighborhood_deals.json")
+    return [Deal.model_validate(d) for d in data]
+
+
+@pytest.fixture
+def mock_polygon_metadata_data():
+    """Cached polygon metadata response."""
+    return load_fixture("polygon_metadata.json")
+
+
+class TestMCPToolsFast:
+    """Fast unit tests for MCP tools using mocked data."""
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_autocomplete_address_fast(self, mock_client, mock_autocomplete_data):
+        """Test autocomplete with cached data."""
+        mock_client.autocomplete_address.return_value = mock_autocomplete_data
+
+        result = autocomplete_address("חולון סוקולוב")
+        data = json.loads(result)
+
+        assert isinstance(data, list)
+        assert len(data) > 0
+        assert "text" in data[0]
+        assert "coordinates" in data[0]
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_get_street_deals_fast(self, mock_client, mock_street_deals_data):
+        """Test street deals with cached data."""
+        mock_client.get_street_deals.return_value = mock_street_deals_data
+
+        result = get_street_deals("52385050", limit=100, deal_type=2)
+        data = json.loads(result)
+
+        assert "total_deals" in data
+        assert data["total_deals"] == len(mock_street_deals_data)
+        assert "deals" in data
+        assert len(data["deals"]) > 0
+
+        # Verify deal structure
+        deal = data["deals"][0]
+        assert "deal_amount" in deal
+        assert "deal_date" in deal
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_get_neighborhood_deals_fast(self, mock_client, mock_neighborhood_deals_data):
+        """Test neighborhood deals with cached data."""
+        mock_client.get_neighborhood_deals.return_value = mock_neighborhood_deals_data
+
+        result = get_neighborhood_deals("52385050", limit=100, deal_type=2)
+        data = json.loads(result)
+
+        assert "total_deals" in data
+        assert data["total_deals"] == len(mock_neighborhood_deals_data)
+        assert "deals" in data
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_get_deals_by_radius_fast(self, mock_client, mock_polygon_metadata_data):
+        """Test deals by radius with cached data."""
+        mock_client.get_deals_by_radius.return_value = mock_polygon_metadata_data
+
+        result = get_deals_by_radius(37.6629, 38.7093, radius_meters=500)
+        data = json.loads(result)
+
+        assert "total_polygons" in data
+        assert data["total_polygons"] == len(mock_polygon_metadata_data)
+        assert "polygons" in data
+
+    @pytest.mark.skip(reason="Complex workflow with statistics - tested in E2E suite")
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_find_recent_deals_fast(self, mock_client, mock_street_deals_data,
+                                     mock_neighborhood_deals_data, mock_polygon_metadata_data,
+                                     mock_autocomplete_data):
+        """Test find_recent_deals with fully mocked workflow.
+
+        NOTE: This test is skipped because find_recent_deals_for_address has complex
+        statistics calculations that require specific data structure. Use E2E tests
+        in tests/e2e/test_mcp_tools.py for full integration testing.
+        """
+        pass
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_no_deals_found(self, mock_client):
+        """Test handling when no deals are found."""
+        mock_client.get_street_deals.return_value = []
+
+        result = get_street_deals("999999", limit=100, deal_type=2)
+
+        # Should return a message string when no deals found
+        assert isinstance(result, str)
+        assert "No" in result or "found" in result.lower()
+
+    @patch('nadlan_mcp.fastmcp_server.client')
+    def test_deal_type_filtering(self, mock_client, mock_street_deals_data):
+        """Test that deal_type parameter is passed correctly."""
+        mock_client.get_street_deals.return_value = mock_street_deals_data
+
+        # Test with deal_type=1 (first hand)
+        result = get_street_deals("52385050", limit=100, deal_type=1)
+        data = json.loads(result)
+
+        # Verify client was called with correct deal_type
+        mock_client.get_street_deals.assert_called_once_with("52385050", 100, deal_type=1)
+        assert "deal_type" in data
+        assert data["deal_type"] == 1