Connecting AI Agents to MetaTrader 5 Through an MCP Server
Summary
The article explains how to build a local Model Context Protocol server that lets compatible AI clients request data from, and send trading operations to, a MetaTrader 5 terminal. It describes a four-part structure: mappings between readable labels and terminal constants, a client wrapper for connection and data conversion, handlers for account, market data, positions, orders, and history, and a server that exposes the functions as tools. The example uses Python, the MetaTrader 5 library, and FastMCP over standard input and output.
The document gives implementation guidance and describes the server's tool categories, configuration, and client connection flow. It emphasizes that tool descriptions help guide agent behavior, while the server handles the actual terminal calls. This is an integration pattern, not a trading strategy or evidence of profitable automated decisions. The article notes material constraints: the Python library is Windows-only, operates against a local terminal, and is single-threaded. It recommends thorough testing on a demo account before live use.
Key ideas
- MCP lets compatible AI clients discover and call tools exposed by a server.
- A layered design separates terminal constants, connection utilities, business handlers, and tool registration.
- The example exposes tools for account information, market data, positions, orders, and trade history.
- The server runs locally alongside the MetaTrader 5 terminal and uses standard input and output for communication.
- The integration does not validate trading decisions, and the article notes platform and concurrency limitations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.