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anshika1109

Stock Market Real-Time Analyzer

by anshika1109

šŸ“ˆ 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

Related MCP server: Stock Analyzer MCP

šŸš€ 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

šŸ”‘ API Keys (Optional)

Yahoo Finance works without API keys. For additional sources:

  1. Copy .env.example to .env

  2. Add your API keys:

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

šŸ¤– 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
  1. Restart Claude Desktop

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

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

  4. 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?"

šŸ“Š 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

šŸ—ļø Project Structure

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

šŸ“– Documentation

šŸ”§ Requirements

  • Python 3.9+

  • Internet connection for API access

  • Optional: API keys for Alpha Vantage and Finnhub

šŸ“¦ 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

šŸŽÆ 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

šŸ¤ Contributing

Contributions are welcome! Feel free to:

  • Report bugs

  • Suggest new features

  • Submit pull requests

  • Improve documentation

šŸ“ License

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

šŸ™ Acknowledgments

šŸ“§ Contact

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

āš ļø 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 ā¤ļø for stock market enthusiasts and AI developers

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