PitchLense MCP

""" Command-line interface for PitchLense MCP Package. Provides CLI tools for running the MCP server and performing risk analysis. """ import argparse import json import sys import os from pathlib import Path from typing import Dict, Any from .core.comprehensive_scanner import ComprehensiveRiskScanner from .models.risk_models import StartupData def load_startup_data(file_path: str) -> Dict[str, Any]: """Load startup data from JSON file.""" try: with open(file_path, 'r') as f: return json.load(f) except FileNotFoundError: print(f"Error: File {file_path} not found") sys.exit(1) except json.JSONDecodeError as e: print(f"Error: Invalid JSON in {file_path}: {e}") sys.exit(1) def save_results(results: Dict[str, Any], output_file: str): """Save analysis results to JSON file.""" try: with open(output_file, 'w') as f: json.dump(results, f, indent=2) print(f"Results saved to: {output_file}") except Exception as e: print(f"Error saving results: {e}") def run_comprehensive_analysis(args): """Run comprehensive risk analysis.""" print("🚀 Starting Comprehensive Startup Risk Analysis...") # Load startup data startup_data = load_startup_data(args.input_file) # Initialize scanner scanner = ComprehensiveRiskScanner(api_key=args.api_key) # Run analysis print("📊 Analyzing startup risks across all categories...") results = scanner.comprehensive_startup_risk_analysis(startup_data) # Display results print(f"\n✅ Analysis Complete!") print(f"📈 Overall Risk Level: {results.get('overall_risk_level', 'Unknown')}") print(f"📊 Overall Risk Score: {results.get('overall_score', 0)}/10") print(f"💡 Investment Recommendation: {results.get('investment_recommendation', 'N/A')}") print(f"🎯 Confidence Score: {results.get('confidence_score', 0.0):.2f}") print("\n🚨 Key Concerns:") for i, concern in enumerate(results.get('key_concerns', [])[:3], 1): print(f" {i}. {concern}") print("\n📋 Risk Categories Analyzed:") for category in results.get('risk_categories', []): print(f" • {category.get('category_name', 'Unknown')}: {category.get('overall_risk_level', 'Unknown')} ({category.get('category_score', 0)}/10)") # Save results if output file specified if args.output_file: save_results(results, args.output_file) def run_quick_assessment(args): """Run quick risk assessment.""" print("⚡ Starting Quick Risk Assessment...") # Load startup data startup_data = load_startup_data(args.input_file) # Initialize scanner scanner = ComprehensiveRiskScanner(api_key=args.api_key) # Run quick assessment print("📊 Analyzing critical risk areas...") results = scanner.quick_risk_assessment(startup_data) # Display results print(f"\n✅ Quick Assessment Complete!") print(f"📈 Overall Risk Level: {results.get('overall_risk_level', 'Unknown')}") print(f"📊 Overall Risk Score: {results.get('overall_score', 0)}/10") print(f"📝 Note: {results.get('note', 'N/A')}") # Save results if output file specified if args.output_file: save_results(results, args.output_file) def run_mcp_server(args): """Run the MCP server.""" print("🚀 Starting PitchLense MCP Server...") print("📊 Available Tools:") print(" • comprehensive_startup_risk_analysis - Full risk assessment across all categories") print(" • quick_risk_assessment - Quick assessment of critical risk areas") print("🔧 Make sure to set your GEMINI_API_KEY environment variable") print("=" * 60) try: scanner = ComprehensiveRiskScanner(api_key=args.api_key) scanner.run() except KeyboardInterrupt: print("\n👋 Shutting down MCP server...") except Exception as e: print(f"❌ Error running MCP server: {e}") sys.exit(1) def create_sample_data(args): """Create sample startup data file.""" sample_data = { "name": "TechFlow Solutions", "description": "AI-powered workflow automation platform for small businesses", "industry": "SaaS/Productivity Software", "stage": "Early Growth", "team_size": 8, "founders": ["Sarah Johnson", "Mike Chen"], "funding_raised": 2500000.0, "revenue": 180000.0, "customers": 150, "market_size": "Global SMB productivity market estimated at $15B", "competitors": ["Zapier", "Microsoft Power Automate", "Automation Anywhere"], "additional_info": { "founded": "2022", "headquarters": "San Francisco, CA", "key_features": ["No-code automation", "AI integration", "Multi-platform support"], "target_customers": "Small to medium businesses with 10-500 employees" } } output_file = args.output_file or "sample_startup_data.json" save_results(sample_data, output_file) print(f"📝 Sample startup data created: {output_file}") def main(): """Main CLI entry point.""" parser = argparse.ArgumentParser( description="PitchLense MCP - Professional Startup Risk Analysis", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: # Run comprehensive analysis pitchlense-mcp analyze --input startup_data.json --output results.json # Run quick assessment pitchlense-mcp quick --input startup_data.json # Start MCP server pitchlense-mcp server # Create sample data pitchlense-mcp sample --output my_startup.json """ ) parser.add_argument( "--api-key", help="Gemini API key (defaults to GEMINI_API_KEY environment variable)" ) subparsers = parser.add_subparsers(dest="command", help="Available commands") # Comprehensive analysis command analyze_parser = subparsers.add_parser("analyze", help="Run comprehensive risk analysis") analyze_parser.add_argument("--input", "-i", required=True, help="Input JSON file with startup data") analyze_parser.add_argument("--output", "-o", help="Output JSON file for results") analyze_parser.set_defaults(func=run_comprehensive_analysis) # Quick assessment command quick_parser = subparsers.add_parser("quick", help="Run quick risk assessment") quick_parser.add_argument("--input", "-i", required=True, help="Input JSON file with startup data") quick_parser.add_argument("--output", "-o", help="Output JSON file for results") quick_parser.set_defaults(func=run_quick_assessment) # MCP server command server_parser = subparsers.add_parser("server", help="Start MCP server") server_parser.set_defaults(func=run_mcp_server) # Sample data command sample_parser = subparsers.add_parser("sample", help="Create sample startup data file") sample_parser.add_argument("--output", "-o", help="Output JSON file for sample data") sample_parser.set_defaults(func=create_sample_data) args = parser.parse_args() if not args.command: parser.print_help() sys.exit(1) # Check for API key if not args.api_key and not os.getenv("GEMINI_API_KEY"): print("⚠️ Warning: GEMINI_API_KEY environment variable not set") print(" Set it with: export GEMINI_API_KEY='your_api_key_here'") print(" Or use --api-key argument") print() # Run the selected command args.func(args) if __name__ == "__main__": main()