AI-powered stock analysis and investment recommendations using Langchain, Anthropic Claude, and real-time market data. Built with FastAPI and designed for both REST API and Agent-to-Agent (A2A) communication via the NEST framework.

• Natural Language Processing: Query stocks using company names or natural language
• Real-time Market Data: Current prices, volume, and 6-month historical data via Yahoo Finance
• AI-Powered Analysis: Investment recommendations with confidence scores using Claude
• Comprehensive Logging: Full audit trails and performance monitoring
• Agent Registry: Discoverable agent capabilities and information
• A2A Communication: NEST framework integration for agent-to-agent interactions
• REST API: Full-featured REST endpoints with OpenAPI documentation

• Python 3.9+ (Python 3.10+ recommended for MCP support)
• Anthropic API key
• Git

1. Clone the repository:

git clone https://github.com/DataSup-Engineer/nasdaq-agent.git
cd nasdaq-agent

2. Create and activate virtual environment:

python -m venv venv
source venv/bin/activate  # On macOS/Linux
# or
venv\Scripts\activate  # On Windows

3. Install dependencies:

pip install -r requirements.txt

4. Configure environment:

cp .env.example .env
nano .env  # Edit with your configuration

5. Set required environment variables:

# Required
ANTHROPIC_API_KEY=sk-ant-your-api-key-here
ANTHROPIC_MODEL=claude-3-haiku-20240307

# Optional - NEST A2A
NEST_ENABLED=true
NEST_PORT=6000
NEST_PUBLIC_URL=http://localhost:6000

6. Run the application:

python main.py

The API will be available at http://localhost:8000

Analyze a stock:

curl -X POST http://localhost:8000/api/v1/analyze \
  -H "Content-Type: application/json" \
  -d '{"query": "What do you think about Apple stock?"}'

Check health:

curl http://localhost:8000/health

View API documentation: Open http://localhost:8000/docs in your browser

When NEST is enabled, the agent can communicate with other agents:

curl -X POST http://localhost:6000/a2a \
  -H "Content-Type: application/json" \
  -d '{
    "role": "user",
    "content": {
      "type": "text",
      "text": "Should I buy Tesla?"
    },
    "conversation_id": "test-123"
  }'

Available A2A commands:

• /help - Show available commands
• /status - Check agent status
• /ping - Test connectivity
• Stock queries - Natural language or ticker symbols

• "What do you think about Apple stock?"
• "Should I buy Tesla?"
• "Analyze Microsoft"
• "AAPL"
• "Tell me about NVDA"

All analysis responses include:

• Recommendation: Buy/Hold/Sell
• Confidence Score: 0-100
• Current Price: Real-time market data
• Market Data: Volume, 52-week range, historical performance
• Reasoning: Detailed analysis and key factors
• Risk Assessment: Identified risks and considerations

nasdaq-agent/
├── src/
│   ├── agents/          # LangChain agent implementations
│   ├── api/             # FastAPI application and routers
│   ├── config/          # Configuration management
│   ├── core/            # Core dependencies and utilities
│   ├── mcp/             # Model Context Protocol integration
│   ├── models/          # Data models and schemas
│   ├── nest/            # NEST A2A framework integration
│   └── services/        # Business logic and external services
├── tests/               # Test suite
├── logs/                # Application logs
├── main.py              # Application entry point
└── requirements.txt     # Python dependencies

Required:

• ANTHROPIC_API_KEY - Your Anthropic API key
• ANTHROPIC_MODEL - Claude model to use (default: claude-3-haiku-20240307)

Application:

• HOST - Server host (default: 0.0.0.0)
• PORT - Server port (default: 8000)
• DEBUG - Debug mode (default: false)

NEST A2A:

• NEST_ENABLED - Enable NEST integration (default: false)
• NEST_PORT - A2A server port (default: 6000)
• NEST_PUBLIC_URL - Public URL for A2A endpoint
• NEST_REGISTRY_URL - Agent registry URL
• NEST_AGENT_ID - Unique agent identifier
• NEST_AGENT_NAME - Human-readable agent name

See .env.example for complete configuration options.

For production deployment on AWS EC2, see the comprehensive DEPLOYMENT_GUIDE.md.

Quick deployment:

# On EC2 instance
git clone https://github.com/DataSup-Engineer/nasdaq-agent.git
cd nasdaq-agent
sudo ./deploy.sh

The deployment script handles:

• System dependencies installation
• Python environment setup
• Service configuration
• Firewall setup
• Log rotation
• Systemd service creation

Docker support is planned for future releases.

# Run all tests
pytest

# Run with coverage
pytest --cov=src

# Run specific test file
pytest tests/test_agent_bridge_a2a.py

# Format code
black src/ tests/

# Lint code
flake8 src/ tests/

# Run with auto-reload
python main.py  # Set DEBUG=true in .env

# Or use uvicorn directly
uvicorn main:main --reload --host 0.0.0.0 --port 8000

• GET / - API information and available endpoints
• GET /health - Health check
• GET /status - Detailed system status
• GET /docs - Interactive API documentation (Swagger UI)
• GET /redoc - Alternative API documentation (ReDoc)

• POST /api/v1/analyze - Analyze a stock with natural language query
• GET /api/v1/agent/info - Get agent information and capabilities

• POST /a2a - Agent-to-Agent communication endpoint

Application logs are stored in logs/:

• analyses.jsonl - Stock analysis requests and responses
• errors.jsonl - Error logs

# Quick health check
./health_check.sh

# Detailed status
curl http://localhost:8000/status

When NEST is enabled, monitor A2A communication:

# Check NEST status
./scripts/monitor_nest.sh

# View A2A logs
tail -f logs/nest_a2a.log

Service won't start:

• Check ANTHROPIC_API_KEY is set correctly
• Verify port 8000 is not in use: lsof -i :8000
• Check logs: tail -f logs/errors.jsonl

NEST A2A not working:

• Verify NEST_ENABLED=true in .env
• Check port 6000 is open in firewall
• Ensure python-a2a is installed: pip show python-a2a
• Check NEST logs for errors

Import errors with python-a2a:

• Ensure you're using python-a2a 0.5.10+
• Verify imports use run_server not serve
• Reinstall: pip install --upgrade python-a2a

# Validate environment configuration
./validate_env.sh .env

# Test API endpoints
curl http://localhost:8000/health
curl http://localhost:8000/api/v1/agent/info

• FastAPI - Modern web framework
• Uvicorn - ASGI server
• LangChain - LLM orchestration
• Anthropic - Claude AI integration
• yfinance - Market data
• Pydantic - Data validation

• python-a2a - NEST A2A framework (requires Python 3.10+)
• mcp - Model Context Protocol (requires Python 3.10+)

See requirements.txt for complete dependency list.

Contributions are welcome! Please follow these guidelines:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Submit a pull request

[Add your license here]

For issues, questions, or contributions:

• Check the DEPLOYMENT_GUIDE.md for deployment issues
• Review logs in logs/ directory
• Open an issue on GitHub

• Built with LangChain
• Powered by Anthropic Claude
• Market data from Yahoo Finance
• A2A communication via NEST Framework