📈 Stock Market Real-Time Analyzer with News Sentiment Analysis

A comprehensive Python tool for fetching and analyzing real-time stock market data from multiple public APIs, with integrated news sentiment analysis to understand how news impacts stock prices. Features include a command-line interface, web dashboards, and an MCP (Model Context Protocol) server for AI assistant integration.

✨ Features

• Multi-Source Data Fetching: Get stock data from Yahoo Finance, Alpha Vantage, and Finnhub

• News Sentiment Analysis: Analyze news articles and their impact on stock prices

• News-Price Correlation: Understand if news sentiment aligns with price movements

• Real-Time Analysis: Compare prices and news across different sources

• Multiple Interfaces:

  • Command-line tool for stocks and news

  • Web dashboard (Flask)

  • Standalone HTML dashboard

  • Streamlit dashboard

  • MCP server for AI assistants (Claude, Kiro)

• Comprehensive Data: Price, change, volume, market cap, day high/low, news sentiment, and more

• Easy Integration: Works with Claude Desktop and other MCP-compatible clients

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/YOUR_USERNAME/stock-market-analyzer.git
cd stock-market-analyzer

# Install dependencies
pip install -r requirements.txt

Basic Usage

Stock Prices (Command Line):

python main.py AAPL GOOGL MSFT

News Analysis (Command Line):

# Get recent news
python news_cli.py AAPL

# Analyze sentiment
python news_cli.py AAPL sentiment

# Correlate news with price movement
python news_cli.py AAPL correlate

# Get news summary
python news_cli.py AAPL summary

Standalone Dashboard:

open standalone_dashboard.html

Web Dashboard:

python web_dashboard.py
# Open http://127.0.0.1:8080

🔑 API Keys (Optional)

Yahoo Finance works without API keys. For additional sources:

1. Copy .env.example to .env

2. Add your API keys:

   • Alpha Vantage - Free tier: 25 requests/day

   • Finnhub - Free tier available

cp .env.example .env
# Edit .env and add your keys

🤖 MCP Server Integration

Use this tool with AI assistants like Claude Desktop or Kiro.

Setup for Claude Desktop

1. Run the setup script:

./setup_claude_desktop.sh

2. Restart Claude Desktop

3. Ask Claude: "Get the stock price for AAPL"

4. Ask Claude: "Analyze news sentiment for TSLA"

5. Ask Claude: "Why did AAPL stock go up today?"

See CLAUDE_DESKTOP_SETUP.md for detailed instructions.

Setup for Kiro

The MCP server is pre-configured in .kiro/settings/mcp.json. Just restart Kiro and ask:

• "Get the stock price for AAPL"

• "Compare TSLA across all sources"

• "What's the news sentiment for NVDA?"

• "Why did GOOGL stock drop today?"

📊 Available Tools

Command Line - Stock Prices

# Single stock
python main.py AAPL

# Multiple stocks
python main.py AAPL GOOGL MSFT TSLA

# Interactive mode
python main.py

Command Line - News Analysis

# Get recent news articles
python news_cli.py AAPL news

# Analyze overall sentiment
python news_cli.py AAPL sentiment

# Correlate news with price movement
python news_cli.py AAPL correlate

# Get formatted summary
python news_cli.py AAPL summary

MCP Server Tools

When integrated with AI assistants, you get access to:

Stock Data:

1. get_stock_quote - Get quote from specific sources

2. compare_stock_sources - Compare data across all sources

3. get_best_quote - Get most reliable quote

4. get_multiple_quotes - Get quotes for multiple symbols

News Analysis: 5. get_stock_news - Get recent news articles 6. analyze_news_sentiment - Analyze overall sentiment 7. correlate_news_with_price - Correlate news with price movement 8. get_news_summary - Get formatted news summary

🏗️ Project Structure

.
├── analyzer.py              # Core stock analysis logic
├── news_analyzer.py         # News sentiment analysis
├── data_sources.py          # Stock API integrations
├── news_sources.py          # News API integrations
├── config.py                # Configuration management
├── main.py                  # CLI interface for stocks
├── news_cli.py              # CLI interface for news
├── mcp_server.py            # MCP server for AI integration
├── web_dashboard.py         # Flask web server
├── dashboard.py             # Streamlit dashboard
├── standalone_dashboard.html # Browser-only version
├── templates/
│   └── index.html           # Web dashboard UI
├── .kiro/settings/
│   └── mcp.json             # Kiro MCP configuration
└── requirements.txt         # Python dependencies

📖 Documentation

• MCP Setup Guide - Detailed MCP server configuration

• Claude Desktop Setup - Claude Desktop integration

• Workflow Diagram - Complete data flow explanation

• Quick Start Guide - Getting started quickly

🔧 Requirements

• Python 3.9+

• Internet connection for API access

• Optional: API keys for Alpha Vantage and Finnhub

📦 Dependencies

• requests - HTTP requests

• pandas - Data manipulation

• yfinance - Yahoo Finance API

• python-dotenv - Environment variables

• flask - Web dashboard (optional)

• streamlit - Streamlit dashboard (optional)

• mcp - Model Context Protocol server

🎯 Use Cases

• Real-time stock monitoring - Track multiple stocks simultaneously

• Price comparison - Verify prices across different data sources

• News sentiment analysis - Understand market sentiment from news

• News-price correlation - See if news explains price movements

• AI assistant integration - Ask AI for stock data and news analysis in natural language

• Data analysis - Export data for further analysis

• Portfolio tracking - Monitor your investments with news context

🤝 Contributing

Contributions are welcome! Feel free to:

• Report bugs

• Suggest new features

• Submit pull requests

• Improve documentation

📝 License

MIT License - feel free to use this project for personal or commercial purposes.

🙏 Acknowledgments

• Yahoo Finance - Primary data source

• Alpha Vantage - Financial data API

• Finnhub - Stock market data

• Model Context Protocol - AI integration standard

📧 Contact

For questions or support, please open an issue on GitHub.

⚠️ Disclaimer

This tool is for informational purposes only. Stock market data may be delayed. Always verify information before making investment decisions. Not financial advice.

Made with ❤️ for stock market enthusiasts and AI developers