Rishi's Interactive Resume MCP Server

#!/usr/bin/env python3 """ Quick Start Demo for Rishi's Resume Server Run this to see example interactions with the resume """ import json import time from pathlib import Path # Load resume data with open("resume_data.json", "r") as f: resume_data = json.load(f) def print_section(title): """Print a formatted section header""" print(f"\n{'='*60}") print(f" {title}") print(f"{'='*60}\n") def simulate_query(question, response_generator): """Simulate a query with timing""" print(f"❓ Question: {question}") start = time.time() response = response_generator() elapsed = (time.time() - start) * 1000 print(f"💬 Response: {response}") print(f"⏱️ Response time: {elapsed:.0f}ms\n") return response def demo_ai_experience(): """Demo AI/ML experience queries""" print_section("🤖 AI/ML EXPERIENCE") # Query 1: AI Models simulate_query( "What AI models has Rishi built?", lambda: f"Rishi built an ML-powered underwriting model at Justworks achieving {resume_data['ai_experience']['models_built'][0]}. " f"He's also championed AI adoption using tools like {', '.join(resume_data['ai_experience']['tools_used'])}." ) # Query 2: AI Leadership simulate_query( "How has Rishi championed AI adoption?", lambda: "Rishi has led AI adoption through: " + ", ".join(resume_data['ai_experience']['initiatives_led'][:2]) ) def demo_business_impact(): """Demo business impact queries""" print_section("💰 BUSINESS IMPACT") # Revenue Impact simulate_query( "What revenue has Rishi generated?", lambda: f"Key revenue impacts: {', '.join(resume_data['key_metrics']['revenue_impact'])}" ) # Efficiency Gains simulate_query( "What efficiency improvements has Rishi delivered?", lambda: f"Major efficiency gains: {', '.join(resume_data['key_metrics']['efficiency_gains'][:3])}" ) def demo_experience_search(): """Demo experience searching""" print_section("🏢 EXPERIENCE SEARCH") # Company search company = "Justworks" exp = next((e for e in resume_data['experience'] if company in e['company']), None) if exp: simulate_query( f"Tell me about Rishi's role at {company}", lambda: f"{exp['title']} at {exp['company']} ({exp['duration']}). " f"Key achievement: {exp['achievements'][0]['description'] if exp['achievements'] else 'Multiple achievements'}" ) def demo_fit_for_role(): """Demo fit for AI PM role""" print_section("🎯 FIT FOR AI PM ROLE") simulate_query( "Why is Rishi a great fit for an AI PM role?", lambda: "Top reasons: " + " | ".join(resume_data['unique_value_props']['for_ai_pm_role'][:3]) ) def show_analytics(): """Show analytics summary""" print_section("📊 ANALYTICS SUMMARY") print("Query Categories Demonstrated:") print(" • AI/ML Experience: 2 queries") print(" • Business Impact: 2 queries") print(" • Company Experience: 1 query") print(" • Role Fit: 1 query") print(f"\nTotal Queries: 6") print(f"Average Response Time: <100ms") print(f"Coverage: All major resume sections") def main(): """Run the complete demo""" print("\n" + "="*60) print(" 🚀 RISHI'S RESUME MCP SERVER - QUICK START DEMO") print("="*60) print("\nThis demo shows example interactions with Rishi's resume.") print("The actual MCP server provides many more query capabilities!\n") input("Press Enter to start the demo...") # Run demos demo_ai_experience() demo_business_impact() demo_experience_search() demo_fit_for_role() show_analytics() print_section("✅ DEMO COMPLETE") print("To run the full MCP server:") print(" 1. Install dependencies: pip install -r requirements.txt") print(" 2. Run server: python server.py") print("\nOr use Docker: docker run -p 8000:8000 rishi-resume-mcp") print("\n🎯 Ready to explore Rishi's qualifications for your AI PM role!") if __name__ == "__main__": main()