Connecting AI Agents to Trading Signals and FMZ Copy Execution

Summary

This article describes two simulated workflows connecting AI-Trader, a cloud agent runtime, and FMZ. In one direction, an agent reads a live FMZ strategy’s output through MCP and publishes a corresponding signal to the signal platform. In the other, it discovers and follows a signal source, then relays incoming signals to an FMZ copy-trading strategy for order execution. The proposed division of duties keeps the agent at the signal layer while FMZ strategies handle exchange execution.

The author reports a demonstration using a Polymarket-related strategy signal and a separate ETH futures copy trade, with example account and signal results. These are illustrations from a test environment, not evidence of profitability or robustness. The article emphasizes that the agent does not receive exchange API keys, but this separation alone does not establish system security or prevent harmful signals. The approach relies on correct API configuration, reliable signal relaying, and suitable controls in the execution strategy; it recommends testing before any live use.

Key ideas

• An agent can relay live strategy data through MCP to a signal publishing platform.
• A separate workflow subscribes to platform signals and forwards them to an FMZ copy-trading strategy.
• The described architecture separates signal selection and communication from exchange order execution.
• The reported trades and account outcomes come from simulated or test use and do not establish profitability.
• Signal quality, integration reliability, and execution controls still require independent evaluation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.