Kite MCP Server Overview

The Kite MCP Server bridges the gap between AI assistants and Zerodha’s Kite trading platform by exposing a full set of trading, market data, and account management tools through the Model Context Protocol. For developers who build AI‑powered financial workflows, this server eliminates the need to write custom API wrappers or handle OAuth flows manually. Instead, a single MCP server delivers a consistent, secure interface that Claude and other AI agents can call with simple tool invocations.

At its core, the server solves two critical problems: authentication and data abstraction. Zerodha’s Kite Connect API requires an OAuth 2.0 flow to obtain short‑lived access tokens, and each request must include proper headers and error handling. The Kite MCP Server encapsulates this complexity inside a local OAuth server that persists tokens, refreshes them automatically, and exposes an tool for agents to verify readiness. Once authenticated, the server offers a rich set of tools—such as , , and —that translate natural language requests into precise API calls, returning structured JSON responses that Claude can use to generate reports, alerts, or trade recommendations.

Key capabilities include:

• Portfolio & Account Management: Retrieve user profile, current positions, long‑term holdings, and margin details with single tool calls.
• Market Data Access: Fetch real‑time quotes, last traded prices, and the full list of tradable instruments, enabling agents to perform market analysis or trend detection.
• Order Lifecycle Control: Place new orders, modify existing ones, and cancel them on demand, allowing dynamic strategy execution driven by AI insights.
• Secure OAuth Flow: Tokens are stored locally, refreshed automatically, and never exposed in logs, ensuring compliance with Zerodha’s security requirements.

Real‑world use cases span from automated day‑trading bots that react to news events, to portfolio optimization assistants that recommend rebalancing actions. In an AI workflow, a Claude user might ask, “What is my current exposure to NIFTY?” The assistant would invoke , parse the response, and present a concise summary. If a sudden market shift occurs, Claude could call to adjust positions without manual intervention. Developers can also extend the server with custom tools or integrate it into larger orchestration pipelines, leveraging MCP’s standardization to keep the AI layer agnostic of underlying trading mechanics.

The server’s architecture—built around single‑responsibility modules such as , , and —ensures maintainability and testability. By exposing a clean MCP interface, it allows AI assistants to treat trading operations as first‑class tools, unlocking new possibilities for data‑driven decision making and rapid prototyping of finance applications.