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

2. Create and activate virtual environment

3. Install dependencies

Configuration

Portfolio Setup

Edit portfolio.json to add your portfolios:

Email Configuration (Optional)

For email reports, create email_config.json:

Usage

Running the MCP Server

Batch Analysis

Analyze all portfolios and generate reports:

Results are saved to batch_financial_charts/

Send Email Reports

Track Recommendations

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

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.