A distributed AI system that combines Model Context Protocol (MCP) with Agent-to-Agent (A2A) communication to provide real-time stock information and analysis.

This project demonstrates the power of combining A2A (Agent-to-Agent) and MCP (Model Context Protocol) architectures to create a practical AI system for stock market information. It features:

• Real-time stock price lookups
• Company ticker symbol searches
• Natural language interaction
• Distributed microservice architecture

The system consists of three main components:

1. MCP Servers

   • Stock MCP: Combined service for stock data and search functionality
   • Handles ticker symbol lookups and real-time price fetching

2. Stock Agent

   • Intermediary service that communicates with MCP servers
   • Processes user queries and formats responses

3. Stock Assistant

   • Main user interface
   • Powered by OpenAI's GPT models
   • Natural language processing for user queries

• Python 3.10 or higher
• Dependencies listed in pyproject.toml:
  • python-a2a[all] >= 0.5.4
  • python-dotenv >= 1.1.0
  • requests >= 2.32.3
  • yfinance >= 0.2.58

1. Clone the repository
2. Create a virtual environment using uv:

uv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

uv install 

uv add package-name

1. Create a .env file in the project root
2. Add your OpenAI API key:

OPENAI_API_KEY=your_api_key_here

1. Start the servers:

python run_servers.py

2. In a separate terminal, run the interactive client:

python interact_client.py

3. Example queries in your terminal:
   • Apple
   • Apple Inc
   • amd

• Provides standardized interfaces for stock data
• Implements DuckDuckGo search for ticker lookup
• Uses YFinance for real-time stock data

• Handles communication between components
• Processes and routes queries
• Formats responses for consistency

• Natural language processing
• Query understanding and decomposition
• Response generation and formatting

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

This project is inspired by the article "The Power Duo: How A2A & MCP Let You Build Practical AI Systems Today".