Overview

Zerodha Trade GPT bridges the gap between conversational AI and live stock trading by exposing a set of MCP tools that let large language models place trades on the Zerodha platform. The server translates natural‑language requests such as “Buy 5 shares of INFY” into authenticated API calls to Zerodha’s Kite Connect, enabling agents like Claude or ChatGPT to execute real‑time buy and sell orders directly from a chat interface. This eliminates the need for manual copy‑paste workflows or separate trading dashboards, allowing developers to embed sophisticated market interactions into their AI‑powered applications.

The server’s core value lies in its secure, structured action model. Each trade is performed through typed MCP tools ( and ) that enforce input validation, authentication, and error handling. Because the tools are part of the MCP ecosystem, any MCP‑compatible agent can invoke them without custom integration code. The backend is built in TypeScript, offering compile‑time safety and a rich SDK that scales with complex trading logic or additional market data feeds. The StdioServerTransport layer ensures low‑latency, bidirectional communication between the AI client and the trading engine, which is critical for time‑sensitive order placement.

Key capabilities include:

• Real‑time order execution: Trades are submitted to Zerodha’s servers within milliseconds of the agent’s request, preserving market timing.
• LLM‑driven input: Agents can interpret user intent from free‑form text, converting it into precise tool calls with structured parameters.
• Secure authentication: The server manages Zerodha API keys and tokens internally, so the AI client never handles sensitive credentials.
• Extensible SDK: Developers can extend the TypeScript SDK to add custom indicators, risk checks, or portfolio management features that run alongside MCP tool calls.

Typical use cases span from autonomous trading bots that react to market news, to educational platforms where students experiment with algorithmic strategies through natural language. In fintech SaaS products, Zerodha Trade GPT can power a “chat‑to‑trade” feature, letting users place orders without leaving the conversation. For research labs, it offers a clean interface to test LLM decision‑making against live market data.

By integrating seamlessly into existing MCP workflows, Zerodha Trade GPT gives developers a single, well‑typed point of entry for executing trades while keeping the AI layer agnostic to underlying API details. Its combination of real‑time execution, secure tooling, and TypeScript robustness makes it a standout solution for anyone looking to combine conversational AI with live equity trading.