Financial Data MCP Server

# Financial Data MCP Server A comprehensive Model Context Protocol (MCP) server for financial data analysis, portfolio management, and automated trading recommendations. ## Features - 📊 **Real-time Stock Data** - Uses free yfinance (Yahoo Finance) API - no API keys required - 💼 **Portfolio Management** - Track multiple portfolios with automated analysis - 📈 **Technical Analysis** - EMA-based trend detection and MACD charts - 🎯 **Trading Signals** - Automated buy/sell recommendations with confidence levels - 📧 **Email Reports** - Automated batch analysis reports with chart attachments - 📉 **Performance Tracking** - Daily monitoring of recommendation performance - 🤖 **MCP Integration** - Full integration with Claude Code and other MCP clients ## Architecture ### Core Components 1. **financial_mcp_server.py** - Main MCP server - Provides MCP tools and resources for financial analysis - Integrates with Claude Code - Real-time stock data via yfinance 2. **batch_fin_mcp_server.py** - Batch analysis engine - Analyzes all portfolios at once - Generates comprehensive reports and charts - Implements 4 trading scenarios based on EMA analysis 3. **email_report_script.py** - Email automation - Sends analysis results via email - Attaches charts and detailed reports - Saves buy recommendations for tracking 4. **daily_tracking_script.py** - Performance tracking - Monitors buy recommendation performance - Creates tracking charts - Generates daily performance reports ## Installation ### 1. Clone the repository ```bash git clone https://github.com/j1c4b/finance_mcp_server.git cd finance_mcp_server ``` ### 2. Create and activate virtual environment ```bash python3 -m venv mcp_fin_server_venv source mcp_fin_server_venv/bin/activate # On Windows: mcp_fin_server_venv\Scripts\activate ``` ### 3. Install dependencies ```bash pip install -r clean_requirements.txt ``` ## Configuration ### Portfolio Setup Edit `portfolio.json` to add your portfolios: ```json { "tech_stocks": { "portfolio": "Technology Giants", "stock_list": ["AAPL", "GOOGL", "MSFT", "AMZN", "META"] }, "dividend_portfolio": { "portfolio": "Dividend Champions", "stock_list": ["JNJ", "PG", "KO", "PEP", "MMM"] } } ``` ### Email Configuration (Optional) For email reports, create `email_config.json`: ```json { "smtp_server": "smtp.gmail.com", "smtp_port": 587, "sender_email": "your_email@gmail.com", "sender_password": "your_app_password", "recipient_emails": ["recipient@example.com"], "subject_prefix": "📊 Financial Analysis Report", "max_attachment_size_mb": 25 } ``` ## Usage ### Running the MCP Server ```bash source mcp_fin_server_venv/bin/activate python3 financial_mcp_server.py ``` ### Batch Analysis Analyze all portfolios and generate reports: ```bash python3 batch_fin_mcp_server.py ``` Results are saved to `batch_financial_charts/` ### Send Email Reports ```bash python3 email_report_script.py ``` ### Track Recommendations ```bash python3 daily_tracking_script.py ``` Results are saved to `tracking_charts/` ## MCP Tools The server provides these tools for Claude Code integration: - `load_portfolio` - Load portfolio data from portfolio.json - `analyze_portfolio` - Detailed analysis of specific portfolio - `portfolio_performance` - Performance metrics over time - `get_stock_info` - Comprehensive stock information - `get_earnings_calendar` - Upcoming earnings announcements - `get_analyst_changes` - Recent analyst upgrades/downgrades - `generate_macd_chart` - MACD technical analysis charts - `get_market_overview` - Major market indices status ## Trading Scenarios The batch analyzer identifies 4 key trading scenarios: - **Scenario A**: Price >10% above 50 EMA → **SELL** signal - **Scenario B**: Price above 50 EMA, touched recently → **BUY** signal - **Scenario C**: Price >5% below 50 EMA, decreasing 3+ days, above 200 EMA → **BUY** signal - **Scenario D**: Price below 50 EMA, touched 200 EMA recently → **BUY** signal ## Technical Analysis - **Trend Detection**: Golden Cross / Death Cross analysis - **EMAs**: 50-day and 200-day exponential moving averages - **MACD**: Moving Average Convergence Divergence charts - **Volume Analysis**: Trading volume patterns - **Confidence Scores**: Each recommendation includes confidence level ## Project Structure ``` finance_mcp_server/ ├── financial_mcp_server.py # Main MCP server ├── batch_fin_mcp_server.py # Batch analysis engine ├── email_report_script.py # Email automation ├── daily_tracking_script.py # Performance tracking ├── portfolio.json # Portfolio configuration ├── requirements.txt # Python dependencies ├── clean_requirements.txt # Cleaned dependencies ├── CLAUDE.md # AI assistant guidance ├── mcp-http-bridge/ # HTTP bridge for MCP ├── batch_financial_charts/ # Generated analysis charts └── tracking_charts/ # Performance tracking charts ``` ## Requirements - Python 3.8+ - yfinance (free Yahoo Finance API) - pandas, numpy, matplotlib - MCP SDK (mcp>=1.0.0) ## Disclaimer ⚠️ **This software is for informational purposes only. It does not constitute financial advice. Always do your own research before making investment decisions.** ## License MIT License - See LICENSE file for details ## Contributing Contributions are welcome! Please feel free to submit a Pull Request. ## Support For issues and questions, please open an issue on GitHub.