Alpaca Trading MCP Server

Alpaca Trading MCP Server

The Alpaca Trading MCP Server bridges the gap between AI assistants and real‑time financial markets by exposing a rich set of Alpaca API endpoints through the Model Context Protocol. Developers can now let Claude or other MCP‑enabled assistants act as a smart trading companion that manages accounts, executes orders, and delivers market insights without leaving the conversational interface. This capability transforms a static chat into an interactive trading desk, enabling rapid prototyping of automated strategies and hands‑on learning for new traders.

At its core, the server offers a clean, REST‑like namespace: resources such as , , and map directly to Alpaca’s account, position, and market data APIs. Tools like or provide imperative actions that the assistant can invoke after a user’s request. By abstracting authentication and HTTP details, the server lets developers focus on business logic while ensuring that every call is authenticated with secure API keys stored in a local file. This design also supports sandbox (paper) trading, allowing safe experimentation before deploying to live markets.

Key capabilities include:

• Comprehensive account visibility – Retrieve balances, portfolio composition, and performance metrics in a single call.
• Flexible order management – Execute market, limit, stop, and stop‑limit orders, cancel pending ones, and close positions programmatically.
• Real‑time market data – Fetch live quotes and historical bars for any tradable symbol, supporting multiple timeframes.
• Asset discovery – List all tradable assets or query detailed metadata for a specific ticker.

Typical use cases span from educational tools that let students practice algorithmic trading with an AI mentor, to production pipelines where a Claude assistant monitors portfolio health and suggests rebalancing actions. Because the server follows MCP conventions, it integrates seamlessly into existing AI workflows: a client can call a resource to obtain data or trigger a tool, and the assistant can interpret the response and respond contextually.

What sets this MCP apart is its dual focus on data retrieval and action execution within the same protocol surface. Developers gain a single, well‑documented entry point to both read market conditions and act upon them, all while leveraging Claude’s natural language understanding to translate user intent into precise API calls. This combination of declarative resources and imperative tools makes the Alpaca Trading MCP Server a powerful addition to any AI‑augmented trading stack.