Robinhood Portfolio Tracker MCP Server

Robinhood Portfolio Tracker MCP Server

Enables portfolio management, trading, and automated bot operations for Robinhood accounts through MCP tools like get_portfolio, buy_stock, sell_stock, and bot management.

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README

Robinhood Portfolio Tracker (CLI)

This project provides a command-line portfolio tracker for Robinhood with login, portfolio viewing, and basic trading. It also includes a paper-trading mode for safe testing.

Important: Real-money trading is risky. Use paper mode first. You are responsible for your account and regulatory compliance.

Features

  • Login using username/password or device token with session caching
  • View portfolio positions, cash, performance snapshot
  • Place market buy/sell orders (limit support planned)
  • Paper-trading mode with local state file
  • Simple momentum strategy example and rebalance command

Quick Start

  1. Create and activate a virtual environment
python3 -m venv .venv && source .venv/bin/activate
  1. Install dependencies
pip install -r requirements.txt
  1. Set environment variables
export RH_USERNAME="your_email@example.com"
export RH_PASSWORD="your_password"
export RH_DEVICE_TOKEN="your_device_token_optional"
export RH_PAPER="true"  # set to "false" to enable live trading
# Optional: if you already have an access token from the web app
export RH_ACCESS_TOKEN="paste_access_token_here"
export RH_TOKEN_TYPE="Bearer"
  1. Run the CLI
python -m robinhood_tracker --help

Commands

  • login: Authenticate and cache session
  • portfolio: Display positions, equity, and cash
  • buy --symbol AAPL --quantity 1: Market buy
  • sell --symbol AAPL --quantity 1: Market sell
  • rebalance --symbols AAPL,MSFT,GOOGL --allocations 40,30,30: Example strategy

Trading Bot Commands

  • bot add --symbol AAPL --quantity 10 --stop-loss -5.0 --take-profit 10.0: Add position to monitor
  • bot remove --symbol AAPL: Remove position from monitoring
  • bot start --interval 5: Start bot (checks every 5 minutes)
  • bot stop: Stop the bot
  • bot status: Show monitored positions and current P&L
  • bot check: Manually check all positions once

MCP (Model Context Protocol) Integration

The project includes a comprehensive MCP adapter for AI model integration.

Available Tools

The MCP adapter provides 15 trading and portfolio management tools:

Portfolio Management

  • get_portfolio - Get portfolio summary and positions
  • get_health - Check API server status
  • login - Authenticate with Robinhood

Trading Operations

  • buy_stock - Buy shares with symbol and quantity
  • sell_stock - Sell shares with symbol and quantity
  • rebalance_portfolio - Auto-rebalance to target allocations

Trading Bot Management

  • get_bot_status - Get bot status and monitored positions
  • add_bot_position - Add position with stop-loss/take-profit
  • remove_bot_position - Remove position from monitoring
  • start_bot - Start automated trading bot
  • stop_bot - Stop automated trading bot
  • check_bot_positions - Manually check all positions

Options Trading

  • get_options_positions - Get current options holdings
  • get_options_orders - Get recent options orders
  • get_options_instruments - Get available options for symbol

Usage Examples

# List all available tools
python3 mcp_robinhood_adapter.py --list-tools

# Get portfolio
python3 mcp_robinhood_adapter.py --tool get_portfolio

# Buy stock
python3 mcp_robinhood_adapter.py --tool buy_stock --params '{"symbol": "AAPL", "quantity": 1}'

# Add position to bot
python3 mcp_robinhood_adapter.py --tool add_bot_position --params '{"symbol": "AAPL", "quantity": 1, "stop_loss": 5, "take_profit": 10}'

AI Model Integration

Configure your AI model to use the MCP server:

{
  "mcpServers": {
    "robinhood": {
      "command": "python3",
      "args": ["/path/to/robinhood_tracker/mcp_robinhood_adapter.py"]
    }
  }
}

Security Notes

  • Never commit credentials. Use environment variables or a .env file not tracked by git.
  • Paper mode writes local state to .paper_state.json.
  • MCP server communicates with Python backend via local HTTP API (127.0.0.1:5000).

Disclaimer

This is not financial advice. Use at your own risk.

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