What problem does it solve? Setting up and using Alpaca's Trading API through AI assistants requires correct MCP server configuration across different clients, and users need guidance on placing trades, fetching market data, and managing accounts through natural language without writing API integration code. ## Core Features & Use Cases - MCP Client Configuration: Step-by-step setup for Claude Desktop, Cursor, VS Code, PyCharm, and Docker with environment variable management for API keys and paper/live trading modes. - Natural Language Trading: Place market, limit, stop, and bracket orders for stocks, ETFs, crypto, and multi-leg options strategies through conversational prompts. - Market Data & Account Management: Retrieve real-time quotes, historical bars, option chains, Greeks, portfolio history, and watchlists, with toolset filtering via ALPACA_TOOLSETS. - Use Case: A developer configures the server in Cursor with paper trading keys, then asks the assistant to buy 10 shares of AAPL at market price, check buying power, and create a tech stocks watchlist without touching the Alpaca API directly. ## Quick Start Set up the Alpaca MCP server in my IDE with my paper trading API keys and show me how to place a test stock order.
