What is Mcp Trading System

The MCP Trading System is a sophisticated multi-agent trading simulation platform that enables multiple AI traders to operate within a simulated market environment, providing real-time visualization of trading activities and portfolio performance.

Use cases

Use cases include simulating trading strategies, analyzing portfolio performance, training AI trading agents, conducting research on market behavior, and providing a platform for educational purposes in finance and trading.

How to use

To use the MCP Trading System, install the required dependencies using ‘pip install -r requirements.txt’, set up any necessary environment variables, and run the application with ‘python app.py’. The web interface will then launch in your default browser, displaying the trading dashboard.

Key features

Key features include multiple AI traders operating simultaneously, real-time portfolio tracking and visualization, detailed transaction history, live trading logs, an interactive web interface built with Gradio, market simulation with price updates, and comprehensive account management.

Where to use

The MCP Trading System can be used in fields such as financial trading, algorithmic trading research, educational purposes for understanding trading strategies, and simulation of market dynamics for testing AI trading agents.

title: MCP
app_file: app.py
sdk: gradio
sdk_version: 5.31.0

MCP Trading System

A sophisticated multi-agent trading simulation system that allows multiple AI traders to operate in a simulated market environment. The system provides real-time visualization of trading activities, portfolio performance, and market interactions.

Features

• Multiple AI traders operating simultaneously
• Real-time portfolio value tracking and visualization
• Detailed transaction history and holdings management
• Live trading logs with color-coded events
• Interactive web interface built with Gradio
• Market simulation and price updates
• Account management and transaction tracking

System Components

• Trading Interface: Web-based UI showing trader performance, holdings, and transactions
• Market Simulation: Real-time market data and price updates
• Account Management: Portfolio tracking and transaction history
• Trading Agents: AI-powered trading strategies
• Logging System: Comprehensive activity logging and monitoring

Dependencies

• gradio
• pandas
• plotly
• python-dotenv
• openai
• asyncio
• requests
• openai-agents
• polygon-api-client

Getting Started

1. Install the required dependencies:

   pip install -r requirements.txt
   

2. Set up your environment variables (if required)

3. Run the application:

   python app.py
   

The web interface will be launched in your default browser, showing the trading dashboard.

Project Structure

• app.py: Main application and UI components
• trading_floor.py: Trading environment and agent management
• market.py: Market simulation and price updates
• accounts.py: Account management and portfolio tracking
• database.py: Data persistence and logging
• traders.py: Trading agent implementations
• util.py: Utility functions and helpers

Monitoring

The system provides real-time monitoring of:

• Portfolio values
• Trading activities
• Market movements
• Agent decisions
• Transaction history

License

[Add your license information here]

Contributing

[Add contribution guidelines here]