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Financial Data MCP Server

by j1c4b
GitHub
Python
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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

git clone https://github.com/j1c4b/finance_mcp_server.git cd finance_mcp_server

2. Create and activate virtual environment

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

pip install -r clean_requirements.txt

Configuration

Portfolio Setup

Edit portfolio.json to add your portfolios:

{ "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:

{ "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

source mcp_fin_server_venv/bin/activate python3 financial_mcp_server.py

Batch Analysis

Analyze all portfolios and generate reports:

python3 batch_fin_mcp_server.py

Results are saved to batch_financial_charts/

Send Email Reports

python3 email_report_script.py

Track Recommendations

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.

This server cannot be installed

-
security - not tested
F
license - not found
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quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Provides real-time stock data analysis, portfolio management, technical analysis with EMA/MACD indicators, and automated trading recommendations with confidence levels using Yahoo Finance API.

  1. Features
    1. Architecture
      1. Core Components
    2. Installation
      1. 1. Clone the repository
      2. 2. Create and activate virtual environment
      3. 3. Install dependencies
    3. Configuration
      1. Portfolio Setup
      2. Email Configuration (Optional)
    4. Usage
      1. Running the MCP Server
      2. Batch Analysis
      3. Send Email Reports
      4. Track Recommendations
    5. MCP Tools
      1. Trading Scenarios
        1. Technical Analysis
          1. Project Structure
            1. Requirements
              1. Disclaimer
                1. License
                  1. Contributing
                    1. Support

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