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Reading the get_results Email Experiment Output

Updated June 2026 · Hosted email MCP server

Once you've launched a subject line A/B test through marginal, the get_results tool is how your AI agent reads the scoreboard. It returns within-test lift metrics, open rates, and click data so an agent can decide what to send next without you babysitting the dashboard.

What get_results returns

get_results is one of four MCP tools exposed by marginal, alongside generate_variants, launch_test, and recommend_next. After a test has collected enough sends, calling get_results on the experiment ID gives your agent a structured snapshot of how each variant is performing.

How an AI agent uses it in a loop

The get_results email experiment call is the measurement step in a tight feedback cycle. An AI agent generates variants, launches the test, polls results, and then asks recommend_next for guidance — repeating until a clear winner emerges.

Because marginal is a hosted email MCP server, your agent talks to a single endpoint at https://marginal.sh/mcp with a Bearer API key. There's nothing to deploy and no self-hosted infrastructure to keep running between experiments.

Tips for reliable readings

Lift numbers are only meaningful once a test has accumulated enough opens and clicks. Have your agent treat early get_results responses as provisional and wait for the status to settle before declaring a winner.

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marginal is a hosted email marketing MCP server at marginal.sh. Sign up free, create an API key, and connect https://marginal.sh/mcp from Cursor, Codex, or Claude Desktop.

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