Paper MCP Server

The Paper MCP Server is a dedicated bridge that lets AI coding assistants such as Claude or Cursor tap directly into the Paper trading platform. By exposing a set of high‑level tools—quote retrieval, batch quote lookups, order placement, and portfolio inspection—the server turns raw API calls into concise, declarative actions that an AI can invoke from a prompt. This eliminates the need for developers to write boilerplate HTTP requests, handle authentication, or parse complex responses, allowing them to focus on building trading logic and strategy experiments.

For developers working with AI assistants, the server offers a streamlined workflow: after configuring the API key once in an environment file or IDE‑specific config, the assistant can request real‑time market data with or submit a simulated order using . The tools are designed to mirror the natural language of trading, so prompts like “Get the latest NBBO for AAPL” or “Place a limit buy order for 100 shares of TSLA at $650” translate directly into authenticated API calls. This tight integration is especially valuable for rapid prototyping, educational demonstrations, or automated back‑testing pipelines where speed and reliability are paramount.

Key capabilities include:

• Real‑time market data: Fetch the current NBBO for any supported symbol, or pull a batch of quotes in a single request to reduce latency.
• Simulated order execution: Place market, limit, or stop orders in the Paper sandbox with instant feedback on status and fill details.
• Portfolio insight: Query positions, unrealized P&L, and account metrics to inform strategy adjustments or risk calculations.
• Environment‑aware configuration: Credentials are injected via environment variables, keeping secrets out of source code and allowing seamless CI/CD integration.

Typical use cases span from interactive trading tutorials—where a student asks an AI to “Show me the order book for GOOG” and immediately sees the response—to production‑grade research pipelines that automatically generate orders based on model outputs. Because the server exposes a clean, protocol‑level interface, it can be embedded into larger automation frameworks or used as a sandbox for algorithmic testing before deploying to live markets.

In summary, the Paper MCP Server removes friction between AI assistants and a sophisticated trading API. By providing ready‑made, authenticated tools that map naturally to trading concepts, it empowers developers to build, test, and iterate on strategies with minimal friction, all while maintaining strict control over credentials and execution environments.