Upbit MCP Server

The Upbit MCP server is a purpose‑built bridge between the Upbit cryptocurrency exchange and AI assistants that speak the Model Context Protocol. It exposes a rich set of tools—ranging from real‑time market feeds to account management and order execution—that let LLM agents query, analyze, and act on Upbit data without writing custom API wrappers. By translating raw OpenAPI responses into well‑structured, machine‑readable commands, the server removes the friction that typically accompanies third‑party exchange integration.

What makes this implementation particularly valuable for developers is its SSE (Server‑Sent Events) support. Traditional MCP servers communicate over a bidirectional stream, which can be awkward to wire into workflow engines like n8n or Zapier. The SSE layer provides a unidirectional, low‑latency channel that is natively understood by many web frameworks and automation platforms. This means a developer can drop the server into a Docker Compose stack, expose an SSE endpoint, and immediately start building event‑driven pipelines that react to market changes or order confirmations.

Key capabilities are grouped into three logical layers:

1. Market Data – Tools such as , , and give instant access to price, depth, and historical chart data. The tool even turns these values into shareable PNGs via a simple URL, enabling visual reporting in chat or dashboards.
2. Account & Order Management – With , , , and related helpers, an assistant can perform full‑fledged trading operations. Error handling follows the FastMCP 1.0.0 standard, returning descriptive JSON on failure so that higher‑level logic can decide whether to retry or alert the user.
3. Analysis & Strategy – The and tools bring algorithmic trading into the conversation. An LLM can ask for a MACD signal or run an SMA‑based backtest over a date range, and the server will return quantitative metrics that can be fed back into decision‑making loops.

Real‑world use cases illustrate the server’s power: a chatbot that monitors BTC/USDT and automatically places limit orders when a user‑defined RSI threshold is breached; an automated portfolio review that pulls balances, calculates P&L, and presents a concise narrative via the or prompts; or a data‑science workflow that streams live candles into an n8n node for real‑time anomaly detection.

Because the server is Docker‑ready and adheres to FastMCP 1.0.0, it can be deployed in a CI/CD pipeline or on a cloud VM with minimal configuration. Developers benefit from comprehensive logging, a full suite of prompts to shape agent behavior, and a backtesting engine that supports multiple classic strategies—all without leaving the MCP ecosystem.