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.

Category
Visit Server

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.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured