The Architect's Playbook - Pillar 1: MCP Financial Analyst

Part of The Architect's Playbook Series - Building Production-Grade AI Systems

This is Pillar 1: Standardization, where we master the Model Context Protocol (MCP) by building a production-grade AI Financial Analyst. This isn't another chatbot demo - it's a complete system demonstrating how MCP revolutionizes AI-to-service communication.

🏗️ The Architect's Playbook Series

Five Pillars of Modern AI Architecture:

• Pillar 1: Standardization (MCP) ← You are here
• Pillar 2: Autonomy (Computer Vision Agents)
• Pillar 3: Collaboration (Multi-Agent Systems)
• Pillar 4: Reliability (Production Monitoring)
• Pillar 5: Framework Maturity (Professional SDKs)

✨ What You'll Build

A complete AI Financial Analyst featuring:

• Production MCP Integration: Real JSON-RPC 2.0 protocol communication
• Intelligent Fallback Systems: Professional error handling and recovery
• Live Market Data: Real-time stock prices and portfolio analysis
• Advanced Analytics: Risk assessment, diversification scoring, performance metrics
• Professional UI: Streamlit dashboard with real-time monitoring
• Full Observability: Connection status, response times, error tracking

🌐 Model Context Protocol (MCP)

This project showcases MCP - the "Wi-Fi for AI" - a universal standard for AI-to-service communication:

• Standardized: JSON-RPC 2.0 protocol adopted by OpenAI, Google, Anthropic
• Secure: Built-in authentication and permission management
• Scalable: Plug-and-play architecture for any service
• Production-Ready: Intelligent error handling and fallback systems

MCP Servers Demonstrated:

• Market Data: Professional stock market integration with fallback
• Stripe Payments: Local MCP server for payment analytics
• System Diagnostics: Real-time MCP health monitoring

🛠️ Tech Stack

• Protocol: Model Context Protocol (MCP) with JSON-RPC 2.0
• Agent Framework: LangGraph & LangChain for orchestration
• LLM: OpenAI GPT-4o for reasoning and analysis
• Web UI: Streamlit with real-time monitoring
• Language: Python 3.9+

🚀 Quick Start

Prerequisites

• Python 3.9+
• Node.js 16+ (for Stripe MCP server)
• OpenAI API key

Installation

# Clone the repository
git clone https://github.com/YourUsername/architects-playbook-pillar1.git
cd architects-playbook-pillar1

# Install Python dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env and add your OpenAI API key

Run the Application

# Start the Streamlit app
streamlit run app.py

Optional: For live Stripe data, start the MCP server:

./setup_stripe_mcp.sh

🎯 Key Learning Outcomes

By building this project, you'll master:

1. MCP Protocol Fundamentals: JSON-RPC 2.0 implementation patterns
2. Production Error Handling: Graceful fallbacks and recovery systems
3. AI Agent Orchestration: Using LangGraph for complex workflows
4. Real-time Monitoring: Building observability into AI systems
5. Professional UI Design: Creating production-grade interfaces

📊 Try These Queries

Market Data:

• "What's the current NIFTY 50 price and performance?"
• "Show me RELIANCE and TCS stock analysis"

Portfolio Analysis:

• "Analyze portfolio: 10 RELIANCE, 5 TCS, 20 HDFC, 15 INFY"
• "Calculate portfolio risk and diversification score"

System Diagnostics:

• "Check MCP system status and server health"
• "Show connection pool metrics and performance"

🔧 Troubleshooting

If you encounter MCP connection issues, see the detailed MCP Troubleshooting Guide.

Common issues:

• MCP Authentication Errors: Expected behavior - demonstrates professional fallback
• Connection Timeouts: System gracefully handles and provides demo data
• Import Errors: Ensure Python 3.9+ and all dependencies installed

🎬 Video Tutorial

Watch the complete tutorial: The Architect's Playbook - Pillar 1

🏗️ Architecture Highlights

Production Patterns Demonstrated:

• JSON-RPC 2.0 protocol implementation
• Intelligent error handling and recovery
• Real-time system monitoring and observability
• Professional data validation and processing
• Scalable agent orchestration with LangGraph

📚 What's Next?

Pillar 2: Autonomy - Computer Vision agents that can see and control your desktop. Same production standards, next-level capabilities.

Subscribe to the channel for the complete Architect's Playbook series!

🤝 Contributing

This is an educational project demonstrating production AI architecture patterns. Feel free to:

• Fork and experiment with different MCP servers
• Extend the monitoring and analytics features
• Add new financial data sources
• Improve the error handling patterns

📄 License

MIT License - Build, learn, and share!

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The Architect's Playbook - Building AI systems that work in production, not just in demos.