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Tiger MCP

šŸ… Tiger MCP System

Python Version License MCP Compatible Docker Support UV Workspace

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Professional-grade Model Context Protocol (MCP) server for Tiger Brokers API integration with Claude AI

Connect Claude AI directly to Tiger Brokers for AI-powered trading, portfolio management, and market analysis. Features 22 MCP tools, REST API access, and enterprise-grade security.


⚔ Quick Installation

Install from GitHub (Recommended)

# Install Tiger MCP pip install git+https://github.com/your-username/tiger-mcp.git # Setup configuration cp tiger_openapi_config.properties.example tiger_openapi_config.properties cp .mcp.json.example .mcp.json # Edit with your Tiger API credentials nano tiger_openapi_config.properties nano .mcp.json # Ready to use!

Use with Claude Code

  1. Install: pip install git+https://github.com/your-username/tiger-mcp.git

  2. Configure .mcp.json with your Tiger API credentials

  3. Restart Claude Code

  4. Start trading: "Show me my Tiger Brokers portfolio"

Use as REST API

import requests response = requests.post("http://server:9000/tiger/get_positions", headers={"Authorization": "Bearer your_api_key"}, json={"account": "your_account_number"} )

✨ Key Features

šŸ¤– AI-Native Trading

  • Claude AI Integration: Direct MCP protocol support for conversational trading

  • Natural Language Processing: Execute trades using natural language commands

  • Intelligent Analysis: AI-powered market analysis and portfolio optimization

  • Risk Management: Automated risk assessment and position sizing

šŸ“Š Real-Time Market Data

  • Live Market Feeds: Real-time quotes, order books, and market depth

  • Historical Analysis: Comprehensive historical data with technical indicators

  • Market Scanning: Advanced screening and filtering capabilities

  • Global Markets: Support for US, HK, SG markets and more

⚔ High-Performance Trading

  • Sub-second Execution: Optimized order routing and execution

  • Portfolio Management: Real-time position tracking and P&L monitoring

  • Risk Controls: Built-in risk management and compliance checks

  • Scalable Architecture: UV workspace with modern async/await patterns

šŸ›”ļø Enterprise Security

  • Encrypted Communication: TLS/SSL encryption for all data transmission

  • Secure Authentication: Tiger Brokers OAuth2 with refresh token management

  • Audit Logging: Comprehensive logging for compliance and debugging

  • Production Ready: Docker containerization with health checks

šŸš€ Quick Start

Prerequisites

  • Python 3.11+ with UV package manager

  • Docker & Docker Compose for containerized deployment

  • Tiger Brokers Account with API access (Apply here)

  • Claude Desktop or Claude API access

⚔ 30-Second Setup

# 1. Clone and setup git clone <your-repository-url> cd tiger-mcp cp .env.template .env # Configure your Tiger API credentials # 2. Install dependencies curl -LsSf https://astral.sh/uv/install.sh | sh # Install UV uv sync # Install all workspace dependencies # 3. Start with Docker docker-compose up -d # 4. Verify installation curl http://localhost:8000/health

šŸ”§ Configuration

Edit .env with your Tiger Brokers credentials:

# Tiger API Configuration TIGER_CLIENT_ID=your_client_id_here TIGER_PRIVATE_KEY=your_private_key_here TIGER_ACCOUNT=your_account_id_here TIGER_SANDBOX=true # Set to false for live trading # Database (using Docker defaults) DATABASE_URL=postgresql://tiger:tiger@localhost:5432/tiger_mcp

āš ļø Security Note: Never commit real credentials to version control. Use .env file for local development and secure environment variables for production.

šŸ¤– Claude AI Integration

Tiger MCP supports both Claude Desktop and Claude Code with comprehensive trading capabilities.

Claude Desktop Configuration

Add Tiger MCP to your Claude Desktop configuration (~/.config/claude/config.json):

{ "mcpServers": { "tiger-mcp": { "command": "uv", "args": ["run", "--package", "mcp-server", "python", "-m", "mcp_server.main"], "cwd": "/path/to/tiger-mcp", "env": { "TIGER_CLIENT_ID": "your_client_id", "TIGER_PRIVATE_KEY": "your_private_key", "TIGER_ACCOUNT": "your_account_id" } } } }

Claude Code Integration

For Claude Code users, Tiger MCP provides enhanced development and trading workflows:

# Configure Claude Code MCP server cp config/claude_mcp.json ~/.config/claude-code/mcp-servers/ # Start the MCP server for Claude Code uv run --package mcp-server python -m mcp_server --claude-code-mode # Use with Claude Code commands claude code analyze-portfolio --account=all claude code backtest-strategy --symbol=AAPL --days=30 claude code risk-assessment --portfolio

Claude Code Features:

  • Code-Driven Trading: Generate and execute trading algorithms

  • Portfolio Analysis: Automated portfolio analysis and reporting

  • Strategy Development: Backtest and optimize trading strategies

  • Risk Management: Code-based risk analysis and position sizing

  • Multi-Account Operations: Manage multiple Tiger accounts programmatically

šŸŽÆ Example Conversations

General Trading (Claude Desktop & Claude Code):

šŸ’¬ "Show me my portfolio performance this week" šŸ’¬ "What are the top gainers in tech stocks today?" šŸ’¬ "Buy 100 shares of AAPL when it drops below $180" šŸ’¬ "Analyze the risk of my current positions"

Multi-Account Trading:

šŸ’¬ "Show portfolio for account account2_id" šŸ’¬ "Compare performance across all my accounts" šŸ’¬ "Switch to trading account account3_id and buy 100 TSLA" šŸ’¬ "What's the total portfolio value across all accounts?"

Claude Code Advanced Usage:

šŸ’¬ "Generate a momentum trading strategy for NASDAQ stocks" šŸ’¬ "Backtest a mean reversion strategy on my current holdings" šŸ’¬ "Create a risk report for all accounts in PDF format" šŸ’¬ "Implement dollar-cost averaging for my portfolio"

šŸ› ļø Available Tools & Capabilities

Tool

Description

Use Case

get_account_info

Account details and balances

Portfolio overview

get_portfolio

Holdings and P&L analysis

Performance tracking

get_market_data

Real-time quotes and data

Market analysis

place_order

Execute trading orders

Order management

scan_market

Market screening tools

Stock discovery

get_historical_data

Historical price data

Backtesting

calculate_indicators

Technical analysis

Chart analysis


šŸ“– Documentation

šŸš€ Getting Started

šŸ”§ Development

šŸš€ Deployment


šŸŽÆ Use Cases

šŸ’¼ Portfolio Management

  • Real-time portfolio tracking and performance analysis

  • Automated rebalancing and risk management

  • Multi-account portfolio consolidation

  • Tax-loss harvesting optimization

šŸ“ˆ Algorithmic Trading

  • Strategy backtesting with historical data

  • Automated order execution based on technical indicators

  • Custom alert systems for market opportunities

  • High-frequency trading with sub-second latency

šŸ” Market Research

  • Advanced market scanning and stock screening

  • Fundamental and technical analysis automation

  • Sector rotation and correlation analysis

  • Options strategy analysis and optimization

šŸ¤– AI-Powered Insights

  • Natural language queries for market data

  • Automated report generation and analysis

  • Risk assessment and scenario modeling

  • Intelligent trade recommendations


šŸ—ļø Architecture

Tiger MCP is built using a modern, scalable architecture:

graph TB Claude[Claude AI] --> MCP[MCP Server] MCP --> Tiger[Tiger Brokers API] MCP --> DB[(PostgreSQL)] MCP --> Cache[(Redis)] Dashboard[Web Dashboard] --> API[FastAPI Backend] API --> DB API --> Tiger Docker[Docker Compose] --> MCP Docker --> API Docker --> DB Docker --> Cache
  • MCP Server: FastMCP-based server with async/await patterns

  • Database: PostgreSQL with async SQLAlchemy for data persistence

  • Caching: Redis for high-performance data caching

  • Security: JWT authentication with encrypted credentials storage

  • Monitoring: Comprehensive logging and health check endpoints


šŸ¤ Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

Development Process

  1. Fork the repository

  2. Create a feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

Code Standards

  • Python: Black formatting, type hints, docstrings

  • Testing: Minimum 80% test coverage required

  • Documentation: Update docs for any new features

  • Security: Follow security best practices


šŸ“œ License

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


āš ļø Disclaimer

Important: This software is for educational and research purposes. Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance does not guarantee future results. Always consult with financial professionals before making investment decisions.


šŸ†˜ Support & Community


šŸ™ Acknowledgments

  • Tiger Brokers for providing robust API services

  • Anthropic for Claude AI and MCP protocol

  • FastMCP for the excellent MCP framework

  • UV for modern Python package management


⭐ Star this repository if you find it useful!

Built with ā¤ļø for the trading and AI community

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