demo_usage.py•4.09 kB
#!/usr/bin/env python3
"""Demo real-world usage of Documentation Search Enhanced MCP Server"""
import asyncio
from src.documentation_search_enhanced.main import (
compare_library_security, get_learning_path, get_docs,
get_code_examples, semantic_search, suggest_secure_libraries
)
async def demo_scenarios():
print("🚀 REAL-WORLD USAGE DEMOS")
print("=" * 60)
# Scenario 1: Developer choosing a web framework
print("\n📌 SCENARIO 1: Choosing a Secure Web Framework")
print("-" * 40)
frameworks = ["django", "flask", "fastapi", "tornado"]
print("Comparing security of popular Python web frameworks...")
result = await compare_library_security(frameworks, "PyPI")
print("\nSecurity Rankings:")
for lib in result['comparison_results']:
print(f" {lib['rank']}. {lib['library']}: {lib['security_score']}/100 {lib['rating']}")
print(f"\n💡 Recommendation: {result['overall_recommendation']}")
# Scenario 2: Learning React from scratch
print("\n\n📌 SCENARIO 2: Learning React Development")
print("-" * 40)
path = await get_learning_path("react", "beginner")
print(f"Generated {path['total_topics']}-step learning path:")
print(f"Estimated time: {path['estimated_total_time']}")
print("\nYour learning journey:")
for step in path['learning_path']:
print(f" {step['step']}. {step['topic']} → Use {step['target_library']} docs")
# Scenario 3: Finding authentication solution
print("\n\n📌 SCENARIO 3: Implementing JWT Authentication in FastAPI")
print("-" * 40)
# Search for authentication docs
docs = await get_docs("JWT authentication tutorial", "fastapi")
print(f"✅ Found comprehensive documentation ({len(docs)} chars)")
# Get specific code examples
examples = await get_code_examples("fastapi", "JWT authentication", "python")
print(f"✅ Found {examples['total_examples']} code examples")
# Scenario 4: Setting up monitoring
print("\n\n📌 SCENARIO 4: Setting Up Production Monitoring")
print("-" * 40)
print("Finding Prometheus monitoring setup guides...")
monitoring_docs = await semantic_search(
"kubernetes cluster monitoring setup",
"prometheus",
"production monitoring infrastructure"
)
if monitoring_docs['results']:
print(f"✅ Found {monitoring_docs['total_results']} relevant guides:")
for result in monitoring_docs['results'][:3]:
print(f" • {result['title']}")
print(f" Relevance: {result['relevance_score']:.1f}%, Read time: {result['estimated_read_time']}")
# Scenario 5: Data science library selection
print("\n\n📌 SCENARIO 5: Choosing Secure Data Science Libraries")
print("-" * 40)
suggestions = await suggest_secure_libraries("data", include_security_score=True)
print("Secure data science library recommendations:")
for lib in suggestions['suggestions'][:5]:
if lib.get('security_score'):
print(f" • {lib['library']} {lib['security_badge']} Score: {lib['security_score']}/100")
# Summary
print("\n\n💡 KEY BENEFITS DEMONSTRATED:")
print("-" * 40)
print("✅ Security-first library selection")
print("✅ Structured learning paths with multi-library integration")
print("✅ Quick access to relevant documentation")
print("✅ Production-ready monitoring and DevOps tools")
print("✅ Smart search with relevance scoring")
async def main():
print("🎯 Documentation Search Enhanced MCP - Real-World Demos")
print("This demo shows how developers actually use this tool\n")
await demo_scenarios()
print("\n\n📚 AVAILABLE FOR 104 LIBRARIES!")
print("Including: React, Vue, FastAPI, Django, Flask, MongoDB, PostgreSQL,")
print("Docker, Kubernetes, Prometheus, Grafana, Elasticsearch, and many more!")
print("\n🚀 Ready to use with Claude Desktop, Cursor, or any MCP client!")
if __name__ == "__main__":
asyncio.run(main())