Building a Robinhood Trading MCP Risk Gateway with TypeScript
AI agents can now do more than answer questions. They can interact with external applications through tools. Robinhood's Trading MCP is one example: an external AI agent can connect to Robinhood and use supported account, portfolio, market-data, watchlist, equities, options, crypto, scanner, alert, and order-related tools. Robinhood also provides trade-approval controls for agentic trading. That…
The article discusses the creation of a Robinhood Trading MCP Risk Gateway with TypeScript. The gateway is designed to ensure deterministic controls between an AI agent and trading execution, rather than allowing the AI model to automatically become the final authority over trading limits. The architecture consists of several components, including the AI Agent, Robinhood Trading MCP, Tool Permission Layer, Trade Intent Validation, Risk Gateway, Approval/Policy, Execution, and Audit/State.
The gateway sits between the AI Agent and Robinhood Trading MCP, creating an explicit execution boundary. The project structure is designed to keep it simple, with separate directories for agent-related code and core business logic. The core business rules are kept separate from the AI model, and structured trade intents are used to prevent the rest of the application from consuming free-form model output.
The flow of the system is as follows: Natural Language → AI Agent → Structured Trade Intent → Schema Validation → Risk Validation. The risk policy is deterministic and can be extended later, with core APIs keeping the implementation simple.
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