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Codex MCP Backtesting Integration for Repeatable Strategy Research

A practical Codex integration pattern for repeatable backtest research and safer iteration cycles.

Separate stable and experimental endpoints

Keep one stable endpoint for decision-grade runs and separate experimental endpoints for risky changes.

This simple split prevents accidental cross-contamination of production research.

Standardize output schema

Require the same fields in every result: assumptions, trade stats, and summary metrics.

Without a common schema, comparison becomes storytelling instead of analysis.

Use regression checkpoints

Maintain a small benchmark set of strategies and windows. Re-run after major prompt or engine changes.

If benchmarks drift unexpectedly, stop and investigate before scaling new tests.

Archive the decision trail

Store accepted variants, rejected variants, and rationale. The archive becomes a force multiplier for future prompts.

Teams that preserve context improve faster than teams that only preserve code.

Need a runnable setup?

Open your dashboard, create an API key, and connect your MCP client to start reproducible backtests.

Open dashboard

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