Open Census MCP Server

#!/usr/bin/env python3 """ Database Query Fix - Handle "city" suffix in place names The database stores "Seattle city" but users search for "Seattle" """ def show_database_fix(): """Show the specific database query fix needed""" print("🔧 DATABASE QUERY FIX NEEDED") print("="*40) print("\n🔍 PROBLEM IDENTIFIED:") print("Database stores: 'Seattle city'") print("User searches: 'Seattle, WA'") print("Query fails: name_lower = 'seattle' (doesn't match 'seattle city')") print("\n📁 FILE TO FIX:") print("src/data_retrieval/geographic_handler.py") print("Method: CompleteGeographicHandler._place_state_lookup()") print("\n🔍 FIND (around line 300):") print(""" cursor.execute(''' SELECT place_fips, state_fips, state_abbrev, name, population, lat, lon FROM places WHERE name_lower = ? AND state_abbrev = ? ORDER BY CAST(COALESCE(population, 0) AS INTEGER) DESC LIMIT 1 ''', (place_name.lower(), state_abbrev)) """) print("\n✏️ REPLACE WITH:") print(""" # Try exact match first cursor.execute(''' SELECT place_fips, state_fips, state_abbrev, name, population, lat, lon FROM places WHERE name_lower = ? AND state_abbrev = ? ORDER BY CAST(COALESCE(population, 0) AS INTEGER) DESC LIMIT 1 ''', (place_name.lower(), state_abbrev)) row = cursor.fetchone() if not row: # Try with city suffix cursor.execute(''' SELECT place_fips, state_fips, state_abbrev, name, population, lat, lon FROM places WHERE name_lower = ? AND state_abbrev = ? ORDER BY CAST(COALESCE(population, 0) AS INTEGER) DESC LIMIT 1 ''', (f"{place_name.lower()} city", state_abbrev)) row = cursor.fetchone() """) print("\n🧪 TEST AFTER FIX:") print("Seattle, WA should resolve to:") print(" FIPS: 53063000") print(" Name: Seattle city") print(" Method: database_with_city_suffix") print("\n⚡ HOWEVER - LLM-FIRST APPROACH IS BETTER:") print("Instead of fixing database queries, implement LLM-first resolution") print("LLM knows Seattle = 53:63000 without database lookup") def show_implementation_priority(): """Show which approach to implement first""" print("\n🎯 IMPLEMENTATION PRIORITY") print("="*30) print("\n🥇 OPTION 1 (RECOMMENDED): LLM-First Approach") print(" - Fixes Seattle, Portland, and all major cities instantly") print(" - No database dependency for common locations") print(" - Aligns with your architectural vision") print(" - Enables advanced analytics with batch operations") print(" - Time: 15 minutes to implement") print("\n🥈 OPTION 2 (BANDAID): Database Query Fix") print(" - Only fixes the 'city' suffix issue") print(" - Still database-dependent") print(" - Doesn't address architectural problems") print(" - Won't support advanced use cases well") print(" - Time: 10 minutes to implement") print("\n💡 RECOMMENDATION:") print("Implement LLM-first approach instead of database fix") print("It solves the root cause, not just the symptom") def main(): show_database_fix() show_implementation_priority() print("\n🚀 NEXT STEPS:") print("1. Test fixed LLM approach: python test_llm_first.py") print("2. Implement LLM-first in census_mcp_server") print("3. Test end-to-end: python quick_test_pnw.py") print("4. Move to batch operations for advanced analytics") if __name__ == "__main__": main()