agentic-stock-research-system

mcp
Security Audit
Warn
Health Warn
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 114 GitHub stars
Code Pass
  • Code scan — Scanned 5 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested

No AI report is available for this listing yet.

SUMMARY

A sophisticated multi-agent AI system for analyzing Indian NSE-listed stocks using real-time data, technical indicators, news sentiment, and advanced AI reasoning.

README.md

🔗 Related project: Check out stock-research-agent-api
a CrewAI-based take on this same idea, with role-specific agents, structured/validated outputs, and a FastAPI service layer.
Both projects are actively maintained; this one continues to evolve independently.

📈 NSE Stock Research & Analysis System

A sophisticated multi-agent AI system for analyzing Indian NSE-listed stocks using real-time data, technical indicators, news sentiment, and advanced AI reasoning.

🌟 Features

🤖 Multi-Agent Architecture

  • Stock Finder Agent: Identifies promising NSE stocks based on liquidity, market cap, and momentum
  • Market Data Agent: Gathers real-time pricing, volume, and technical indicators
  • News Analyst Agent: Analyzes recent news sentiment and market impact
  • Recommendation Agent: Provides actionable BUY/SELL/HOLD recommendations with target prices

📊 Advanced Analytics

  • Real-time NSE stock data integration
  • Technical indicators (RSI, Moving Averages, MACD)
  • Volume and volatility analysis
  • News sentiment classification
  • Risk-reward assessment

🎯 Smart Recommendations

  • Specific entry/exit price points
  • Stop-loss levels and risk management
  • Confidence scoring for each recommendation
  • Time horizon-based analysis (short-term to medium-term)

🎨 Modern UI

  • Clean, responsive Streamlit interface
  • Interactive charts and visualizations
  • Real-time status updates
  • CSV export functionality
  • Mobile-friendly design

🚀 Quick Start

Prerequisites

Installation

  1. Clone the repository

    git clone https://github.com/rooneyrulz/agentic-stock-research-system
    cd nse-stock-research-system
    
  2. Install dependencies

    pip install -r requirements.txt
    
  3. Set up environment variables

    cp .env.example .env
    # Edit .env with your API keys
    
  4. Install Bright Data MCP

    npm install -g @brightdata/mcp
    

Running the Application

  1. Start the Streamlit app

    streamlit run streamlit_app.py
    
  2. Access the application

    • Open your browser to http://localhost:8501
    • Enter your API keys in the sidebar
    • Select analysis parameters
    • Click "Start Analysis" and wait for results!

🔧 Configuration

API Keys Setup

Bright Data API Token

  1. Sign up at Bright Data
  2. Navigate to your dashboard
  3. Go to "Zones" → "Web Unlocker"
  4. Copy your API token

OpenAI API Key

  1. Sign up at OpenAI Platform
  2. Go to "API Keys" section
  3. Create a new API key
  4. Copy the key (starts with 'sk-')

Analysis Types

  • Short-term Trading (1-7 days): Focus on momentum, technical breakouts, and news catalysts
  • Medium-term Investment (1-4 weeks): Emphasis on earnings, sector trends, and technical setups
  • General Market Analysis: Broad market overview with top stock picks across sectors

📈 Sample Output

🎯 TRADING RECOMMENDATIONS
═══════════════════════════════════

RELIANCE - Reliance Industries Limited
─────────────────────────────────
📋 RECOMMENDATION: BUY
🎯 TARGET PRICE: ₹2,650
⏰ TIME HORIZON: 1-3 days
📊 CONFIDENCE: HIGH

📈 ENTRY STRATEGY:
Current Price: ₹2,450
Suggested Entry: ₹2,430 - ₹2,460
Stop Loss: ₹2,380 (3.2% below entry)
Target: ₹2,650 (8.2% upside potential)

💡 RATIONALE:
Technical: Breakout above 50-day MA with strong volume
Fundamental: Positive earnings guidance + new project announcements
Risk-Reward: 1:2.6 ratio

🏗️ System Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Streamlit UI  │────│   Supervisor     │────│  Bright Data    │
│                 │    │     Agent        │    │   MCP Server    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                              │
                    ┌─────────┼─────────┐
                    │         │         │
            ┌───────▼───┐ ┌───▼───┐ ┌───▼────┐
            │Stock Finder│ │Market │ │News    │
            │   Agent    │ │Data   │ │Analyst │
            └────────────┘ │Agent  │ │Agent   │
                          └───────┘ └────────┘
                                │
                        ┌───────▼────────┐
                        │ Recommendation │
                        │     Agent      │
                        └────────────────┘

🔍 Agent Details

Stock Finder Agent

  • Scans NSE universe for liquid, high-potential stocks
  • Filters by market cap, volume, and momentum criteria
  • Avoids penny stocks and illiquid securities
  • Focuses on large-cap and mid-cap opportunities

Market Data Agent

  • Real-time price, volume, and market data
  • Technical indicators (RSI, MACD, Moving Averages)
  • Support/resistance level identification
  • Trend analysis and momentum assessment

News Analyst Agent

  • Scrapes recent financial news and announcements
  • Sentiment classification (Positive/Negative/Neutral)
  • Impact assessment on stock prices
  • Catalyst identification for price movements

Recommendation Agent

  • Synthesizes all data into actionable recommendations
  • Provides specific entry/exit strategies
  • Risk management and position sizing guidance
  • Confidence scoring and time horizon analysis

🛡️ Risk Management Features

  • Stop-loss recommendations for every trade suggestion
  • Position sizing guidance based on volatility
  • Risk-reward ratio analysis (minimum 1:2 ratio)
  • Confidence scoring to help with decision making
  • Time horizon specification for each recommendation

📊 Export & Reporting

  • CSV Export: Download analysis results for further analysis
  • Interactive Charts: Visualize current vs target prices
  • Performance Tracking: Monitor recommendation accuracy
  • Historical Analysis: Compare predictions with actual outcomes

⚠️ Important Disclaimers

  • This tool is for educational and research purposes only
  • Always consult with a qualified financial advisor before investing
  • Past performance does not guarantee future results
  • The Indian stock market involves substantial risk of loss
  • Do your own due diligence before making any investment decisions

🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support and questions:

  • Open an issue on GitHub
  • Check the documentation
  • Review the troubleshooting guide below

Troubleshooting

Common Issues:

  1. API Key Errors

    • Ensure your Bright Data token is valid and has sufficient credits
    • Verify OpenAI API key starts with 'sk-' and has available quota
  2. MCP Installation Issues

    # Reinstall MCP globally
    npm uninstall -g @brightdata/mcp
    npm install -g @brightdata/mcp
    
  3. Streamlit Issues

    # Clear Streamlit cache
    streamlit cache clear
    
  4. Import Errors

    # Reinstall dependencies
    pip install -r requirements.txt --force-reinstall
    

🔄 Version History

  • v1.0.0 - Initial release with multi-agent architecture
  • v1.1.0 - Added Streamlit UI and export functionality
  • v1.2.0 - Enhanced recommendation parsing and visualization

Made with ❤️ for the Indian Stock Market Community

Reviews (0)

No results found