fixing some minor bugs that crept in (eg get_bird_sightings was get_bird_sightings_tool in server.py, also an indent error that broke function and dropped a return), making the news search a cascade pattern (like trend etc), updating observation entrypoint, etc

.cursorignore

@@ -0,0 +1,37 @@
+# Dependencies
+node_modules/
+.venv/
+venv/
+__pycache__/
+
+# Data & assets
+*.mp3
+*.wav
+*.mp4
+*.jpg
+*.png
+*.pdf
+data/
+datasets/
+
+# Build artifacts
+dist/
+build/
+*.pyc
+.pytest_cache/
+
+# Old/archived
+**/archived/
+**/old/
+dev_diary/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+
+# Misc
+.DS_Store
+.env
+
+

src/cluas_mcp/news/news_search_entrypoint.py

@@ -146,4 +146,4 @@ def verify_claim(claim: str) -> dict:
         "explanation": f"This is a mock verification result for the claim: '{claim}'. Real implementation would use a fact-checking API to verify the claim.",
         "sources": [],
         "source": "mock_data"
-    }
+    }

src/cluas_mcp/observation/observation_entrypoint.py

@@ -3,7 +3,7 @@ from src.cluas_mcp.observation.ebird import get_bird_sightings, format_sightings
 
 logger = logging.getLogger(__name__)
 
-def get_bird_sightings_tool(location: str = "HuggingFace HQ, Brooklyn, NY") -> dict:
+def get_bird_sightings(location: str = "HuggingFace HQ, Brooklyn, NY") -> dict:
     """
     Get recent bird sightings near a location.
     
@@ -87,3 +87,4 @@ def analyze_temporal_patterns(data_type: str, location: str = "global") -> dict:
         "time_range": "2023-01-01 to 2024-01-15",
         "source": "mock_data"
     }
+

src/cluas_mcp/server.py

@@ -232,8 +232,8 @@ async def call_tool(tool_name: str, arguments: dict) -> list[TextContent]:
     
     # Raven tools
     elif tool_name == "search_news":
-    query = arguments.get("query")
-    if not query:
+        query = arguments.get("query")
+        if not query:
             raise ValueError("query is required for search_news")
         max_results = arguments.get("max_results", 5)
         results = await loop.run_in_executor(None, search_news, query, max_results)
@@ -268,7 +268,7 @@ async def call_tool(tool_name: str, arguments: dict) -> list[TextContent]:
         timeframe = arguments.get("timeframe", "recent")
         results = await loop.run_in_executor(None, get_weather_patterns, location, timeframe)
         formatted = format_weather_patterns(results)
-    return [TextContent(type="text", text=formatted)]
+        return [TextContent(type="text", text=formatted)]
 
     elif tool_name == "analyze_temporal_patterns":
         data_type = arguments.get("data_type")

src/cluas_mcp/web/web_search_entrypoint.py

@@ -141,3 +141,4 @@ def get_quick_facts(topic: str) -> dict:
 
 
 
+