🏠 Home Depot MCP Server - Comprehensive Investment Research

A powerful Model Context Protocol (MCP) server that provides comprehensive investment research and analysis for The Home Depot, Inc. (HD) and related market intelligence.

🚀 What Makes This Server Significantly More Useful

📊 Comprehensive Financial Data

• Real-time stock data from Alpha Vantage and Yahoo Finance

• Financial metrics including P/E ratios, ROE, margins, debt ratios

• Technical analysis with moving averages, RSI, and trend signals

• Valuation analysis with over/under-valued assessments

📰 Market Intelligence & News Analysis

• Multi-source news aggregation from NewsAPI, MarketWatch, Seeking Alpha

• Sentiment analysis with positive/negative/neutral scoring

• Key theme extraction identifying trends in earnings, housing, retail, etc.

• Analyst ratings and price targets

🏠 Economic Context & Impact Analysis

• Housing market indicators (starts, permits, sales, prices)

• Consumer sentiment and spending patterns

• Macroeconomic factors (Fed rates, inflation, unemployment, GDP)

• Home Depot impact scoring based on economic environment

💼 Investment Research & Thesis Building

• Bull/Bear/Neutral case analysis with supporting points

• Risk assessment across financial, operational, market, and regulatory factors

• Competitive analysis vs Lowe's and other competitors

• Investment consensus with confidence scoring

🔧 Advanced Tools & Capabilities

• SEC filings analysis with filtering and document links

• Competitor benchmarking across the home improvement sector

• Technical indicators for trading decisions

• Comprehensive reporting with formatted, actionable insights

🛠️ Available Resources

🎯 Available Tools

🚀 Quick Start

1. Install Dependencies

2. Build the Project

3. Start the Server

4. Test All Features

🔧 Configuration

API Keys Required

Set these environment variables for full functionality:

Free API Alternatives

• Alpha Vantage: Free tier with 500 requests/day

• NewsAPI: Free tier with 1,000 requests/day

• FRED: Free with registration (unlimited requests)

📱 Cursor Integration

Method 1: Cursor Settings

1. Go to Settings → Extensions → MCP

2. Click "Add Server"

3. Use these settings:

   • Name: home-depot

   • Command: node

   • Args: dist/index.js

   • CWD: /path/to/depot-mcp

Method 2: Config File

Create ~/.cursor/mcp-servers.json:

💡 Example Queries

Once connected to Cursor, try these questions:

📊 Financial Analysis

• "Show me Home Depot's current financial metrics"

• "What's the technical analysis for HD stock?"

• "Get Home Depot's valuation analysis"

📰 Market Intelligence

• "What's the latest news sentiment for Home Depot?"

• "Show me recent IR news releases"

• "What upcoming events does Home Depot have?"

🏠 Economic Context

• "How is the housing market affecting Home Depot?"

• "What's the economic impact on HD?"

• "Show me economic indicators relevant to Home Depot"

💼 Investment Research

• "Build me an investment thesis for Home Depot"

• "What are the bull and bear cases for HD?"

• "How does Home Depot compare to competitors?"

• "What are the key risks for Home Depot?"

📄 Regulatory & Compliance

• "Get the last 5 SEC filings for Home Depot"

• "Show me recent 10-K and 10-Q filings"

🏗️ Architecture

🔄 Data Flow

1. MCP Request → Server receives JSON-RPC call

2. Service Layer → Appropriate service processes request

3. API Integration → Fetches data from multiple sources

4. Analysis Engine → Processes and analyzes data

5. Response Formatting → Returns structured, actionable insights

🚨 Error Handling & Fallbacks

• Graceful degradation when APIs are unavailable

• Mock data fallbacks for development and testing

• Comprehensive error logging for debugging

• Cache management to reduce API calls

📈 Performance Features

• Intelligent caching (15-minute cache duration)

• Parallel API calls for faster response times

• Request batching to minimize overhead

• Memory-efficient data processing

🔮 Future Enhancements

• Real-time alerts for price movements and news

• Portfolio tracking and performance analysis

• Advanced charting and visualization tools

• Machine learning sentiment analysis

• WebSocket support for live data streaming

🤝 Contributing

This server demonstrates how to build a comprehensive MCP server that goes far beyond basic data retrieval. Key principles:

1. Multiple data sources for comprehensive coverage

2. Intelligent analysis rather than just data display

3. Actionable insights with clear recommendations

4. Robust error handling and fallback mechanisms

5. Extensible architecture for easy enhancement

📄 License

MIT License - feel free to use this as a template for building your own comprehensive MCP servers!

Transform your MCP server from a simple data fetcher into a powerful investment research platform! 🚀