Zerodha MCP Server

Overview

Zerodha MCP Server is a Golang‑based implementation of the Claude Model Context Protocol (MCP) that bridges AI assistants with Zerodha’s trading ecosystem. By exposing a rich set of tools—ranging from account details and portfolio snapshots to real‑time market data—the server allows Claude, Sonnet, GPT‑4o mini and other MCP‑compatible clients to query live Zerodha Kite data without leaving the conversational interface. This eliminates the need for manual API calls or third‑party dashboards, streamlining research, strategy testing and day‑to‑day trading decisions directly within the AI workflow.

The server solves a common pain point for quantitative developers and active traders: integrating disparate data sources into an AI‑driven decision loop. Instead of juggling separate scripts, API keys, and authentication flows, users can simply authenticate once in the MCP server configuration. Subsequent calls to tools such as , or are handled behind the scenes, returning structured JSON that Claude can parse and reason about. This tight coupling reduces latency, eliminates boilerplate code, and keeps the user’s focus on higher‑level strategy rather than data plumbing.

Key capabilities include:

• Account and margin insights: Retrieve user profile, overall margins, and segment‑specific margin requirements in a single request.
• Portfolio analytics: Access current holdings, day and net positions, and order‑specific margin needs to assess exposure instantly.
• Market feed: Pull last traded prices, detailed quotes, and OHLC data for any instrument, enabling real‑time trend analysis within the chat.
• Instruments discovery: List all available instruments, filter by exchange, or fetch auction‑eligible securities to support research and backtesting.
• Mutual fund integration: View MF instruments, holdings, orders, SIPs and detailed order information—extending coverage beyond equities into the broader investment universe.

Real‑world scenarios that benefit from this server include automated strategy backtesting, on‑the‑fly portfolio rebalancing suggestions, or scenario planning where an AI assistant can fetch live market data and compute risk metrics before proposing a trade. Developers can embed the MCP server in continuous‑integration pipelines, enabling AI‑guided parameter tuning or anomaly detection during live trading sessions.

Integration is straightforward: after configuring the MCP server with Kite API credentials, the AI client (e.g., Claude Desktop) is pointed to the binary via its developer settings. Once authenticated, any supported tool becomes a first‑class function call within the conversation. The server handles OAuth redirection, token refreshes, and error handling internally, presenting a clean, declarative interface to the assistant. This design not only speeds up prototyping but also encourages reproducible, auditable trading workflows that can be shared across teams or deployed in production environments.