Open Census MCP Server

#!/usr/bin/env python3 """ Statistical Advisor Status Check & Integration Guide This script checks if everything is ready for the statistical advisor integration and provides clear next steps. """ import sys import os import json from pathlib import Path # Load environment variables try: from dotenv import load_dotenv # Try multiple .env locations for env_path in [ Path('.env'), Path(__file__).parent / '.env', ]: if env_path.exists(): load_dotenv(env_path) print(f"📄 Loaded .env from: {env_path}") break except ImportError: print("⚠️ python-dotenv not installed - relying on system environment variables") # Setup paths current_dir = Path(__file__).parent kb_path = current_dir / "knowledge-base" src_path = current_dir / "src" def check_files(): """Check if all required files exist""" print("📁 File System Check:") required_files = [ ("LLM Statistical Advisor", kb_path / "llm_statistical_advisor.py"), ("Search Engine", kb_path / "kb_search.py"), ("Geographic Parsing", kb_path / "geographic_parsing.py"), ("Variable Search", kb_path / "variable_search.py"), ("MCP Server", src_path / "census_mcp_server.py"), ] required_dirs = [ ("Variables DB", kb_path / "variables-db"), ("Table Catalog", kb_path / "table-catalog"), ("Methodology DB", kb_path / "methodology-db"), ] optional_files = [ ("Gazetteer DB", kb_path / "geo-db" / "geography.db"), ] all_good = True for name, path in required_files: exists = path.exists() print(f" {'✅' if exists else '❌'} {name}: {path}") if not exists: all_good = False for name, path in required_dirs: exists = path.exists() and path.is_dir() print(f" {'✅' if exists else '❌'} {name}: {path}") if not exists: all_good = False for name, path in optional_files: exists = path.exists() print(f" {'🔧' if exists else '⚠️ '} {name}: {path} ({'present' if exists else 'optional'})") return all_good def check_environment(): """Check environment variables""" print("\\n🔑 Environment Check:") openai_key = os.getenv('OPENAI_API_KEY') anthropic_key = os.getenv('ANTHROPIC_API_KEY') print(f" {'✅' if openai_key else '❌'} OPENAI_API_KEY: {'Present' if openai_key else 'Missing'}") print(f" {'🔧' if anthropic_key else '⚠️ '} ANTHROPIC_API_KEY: {'Present' if anthropic_key else 'Optional'}") if not openai_key: print(" ⚠️ OpenAI API key is required for embeddings and LLM reasoning") return False return True def check_knowledge_base(): """Check knowledge base structure""" print("\\n📚 Knowledge Base Check:") # Check variables database variables_dir = kb_path / "variables-db" if variables_dir.exists(): faiss_file = variables_dir / "variables.faiss" metadata_file = variables_dir / "variables_metadata.json" print(f" {'✅' if faiss_file.exists() else '❌'} Variables FAISS index: {faiss_file.exists()}") print(f" {'✅' if metadata_file.exists() else '❌'} Variables metadata: {metadata_file.exists()}") if metadata_file.exists(): try: with open(metadata_file) as f: metadata = json.load(f) print(f" 📊 Variables count: {len(metadata):,}") except: print(" ⚠️ Could not read metadata file") else: print(" ❌ Variables database directory missing") return False # Check table catalog catalog_dir = kb_path / "table-catalog" if catalog_dir.exists(): catalog_files = list(catalog_dir.glob("table_catalog*.json")) print(f" {'✅' if catalog_files else '❌'} Table catalog files: {len(catalog_files)} found") else: print(" ❌ Table catalog directory missing") return False # Check methodology database methodology_dir = kb_path / "methodology-db" if methodology_dir.exists(): print(f" {'✅' if methodology_dir.exists() else '❌'} Methodology database: present") else: print(" ⚠️ Methodology database missing (optional)") return True def test_imports(): """Test if components can be imported""" print("\\n🔧 Import Test:") sys.path.insert(0, str(kb_path)) sys.path.insert(0, str(src_path)) components = [ ("LLM Statistical Advisor", "llm_statistical_advisor", "LLMStatisticalAdvisor"), ("Search Engine", "kb_search", "create_search_engine"), ("Geographic Parsing", "geographic_parsing", "create_geographic_parser"), ("Variable Search", "variable_search", "create_variables_search"), ] all_imports_good = True for name, module, function in components: try: exec(f"from {module} import {function}") print(f" ✅ {name}: import successful") except Exception as e: print(f" ❌ {name}: import failed - {e}") all_imports_good = False return all_imports_good def provide_next_steps(files_ok, env_ok, kb_ok, imports_ok): """Provide next steps based on status""" print("\\n🎯 Status Summary:") overall_status = files_ok and env_ok and kb_ok and imports_ok print(f" Files: {'✅' if files_ok else '❌'}") print(f" Environment: {'✅' if env_ok else '❌'}") print(f" Knowledge Base: {'✅' if kb_ok else '❌'}") print(f" Imports: {'✅' if imports_ok else '❌'}") print("\\n🚀 Next Steps:") if overall_status: print(" 🎉 ALL SYSTEMS GO! You can now:") print(" 1. Run the integration test:") print(" python3 integration_test.py") print() print(" 2. Test LLM statistical consultation:") print(" python3 test_consultation.py") print() print(" 3. Run the new MCP server (v3.0):") print(" python3 src/census_mcp_server.py") print() print(" 4. Test with new LLM-first architecture in Claude Desktop") else: print(" ❌ Issues detected. Fix these first:") if not files_ok: print(" • Missing required files - check the file paths above") if not env_ok: print(" • Set OPENAI_API_KEY environment variable") print(" export OPENAI_API_KEY='your-key-here'") if not kb_ok: print(" • Knowledge base needs to be built:") print(" cd knowledge-base && python3 build-kb-concept-based.py") if not imports_ok: print(" • Import errors - check Python dependencies:") print(" pip install -r requirements.txt") def main(): """Run the complete status check""" print("🧠 LLM Statistical Advisor Integration Status Check") print("=" * 60) files_ok = check_files() env_ok = check_environment() kb_ok = check_knowledge_base() imports_ok = test_imports() provide_next_steps(files_ok, env_ok, kb_ok, imports_ok) if __name__ == "__main__": main()