Enables AI assistants to create, backtest, and manage automated investment strategies (symphonies) on Composer, including searching through 1000+ existing strategies, monitoring portfolio performance, and executing trades with live market data.
Enables AI agents to run a full quant research workflow over MCP: pulling data, authoring and backtesting strategies, running statistical validation and risk checks, and recording findings for future sessions.
Enables LLMs to access banking, investment, and cryptocurrency data through a standardized MCP interface, featuring Plaid integration for account and transaction data and Robinhood for crypto trading with audit trails.
Enables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.
Enables large language models to interact with Alpaca's trading infrastructure using natural language, supporting stock/options trading, portfolio management, watchlist handling, and real-time market data access.
