
XTester MCP Gives AI Agents a Strategy-Testing Environment
XTester MCP connects an AI agent to a local environment for developing and historically testing strategies, including the project, compiler, market data and test results.
Read noteHow our products are built, what ships in each release, and the decisions we make under the hood. Straight from the EasyTrading team.

Local stdio describes how an MCP client talks to the host, but it does not guarantee a fully local AI process. This guide maps the complete data path and practical security boundaries.
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XTester MCP connects an AI agent to a local environment for developing and historically testing strategies, including the project, compiler, market data and test results.
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An AI agent may improve a strategy only on paper if the data, fees or execution model changed with the code. Here is what to preserve so another run can reproduce the result.
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We compared two ways to copy a position. On one day of data they behaved identically; differences appeared after rounding and changed order-state rules.
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XTester added a supervised Launcher and a guarded Hyperliquid Testnet path, CopyTrader launched Hyperliquid for trade copying, and TradeStat opened a public demo interface. Here are the most important changes and the remaining readiness boundaries.
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The new XTester release helps the AI lab reject non-working candidates earlier and return to a version supported by real trades and fresh out-of-sample evidence.
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We are opening the EasyTrading portal blog. This first article explains how XTester, CopyTrader, and the planned TradeStat service fit together, what works today, and what we will publish here.
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