Integration · Statsig
Statsig is the modern experimentation platform that combines feature flags, experiments, and product analytics in one.
The MCP exposes full CRUD across experiments, gates, dynamic configs, layers, and segments, plus CUPED-adjusted results. The same platform OpenAI, Notion, Brex, and Whatnot use for shipping at speed. The agent runs the platform end-to-end through prompts; the Statsig UI remains for stakeholders who prefer the dashboard.
What you can do via MCP
“List all active experiments and rank by days remaining.”
Pulls running experiments via the Statsig MCP, sorts by remaining duration, and surfaces the ones nearest a decision.
“Find feature gates marked stale and refactor my codebase to remove them.”
Cross-references stale gates with codebase grep results, then opens a PR removing the gate calls and the gate config in one pass.
“Get experiment results for checkout-redesign with CUPED applied.”
Returns variance-reduced results plus confidence intervals; recommends ship/iterate/roll-back based on primary metric movement.
“Create a 50/50 A/B experiment on the pricing page tracking purchase_completed.”
Sets up the experiment with the right targeting, primary metric, and CUPED config; returns the experiment ID and the integration snippet.
“Brainstorm three experiment ideas based on past wins in the onboarding funnel.”
Reads past experiment results from the Statsig project, identifies winning patterns, and proposes follow-on experiments grounded in the data.
Initial experiment creation from a brief. The agent populates the experiment config, sets CUPED on the primary metric, and returns the integration snippet for the SDK.
# Statsig MCP, called via the agent runtime
mcp.statsig.create_experiment({
name: "pricing-page-redesign",
description: "Test new pricing page hierarchy vs control",
primary_metric: "purchase_completed",
cuped: { enabled: true, lookback_days: 30 },
groups: [
{ name: "control", size: 50 },
{ name: "treatment", size: 50 }
],
hypothesis: "New pricing card layout increases purchase completion."
})
# Returns experiment_id, embed snippet, and dashboard URLMCP integration
Visual demonstration
Primary metric: purchase_completed (CUPED)
| Variant | Metric | Lift | 95% CI | p |
|---|---|---|---|---|
| Controlcontrol | 12.40% | baseline | — | — |
| Treatment | 13.71% | +10.56% | [4.20, 17.00] | 0.002 |
CUPED reduced variance by 31%. Effect held across mobile and desktop segments. Recommendation: ship treatment.
pricing-page-redesign
Runningcheckout-button-color
Decided · Shiponboarding-skip-step
Runninghomepage-hero-copy
Decided · IterateCLI alternative
Statsig ships a CLI for build-time gate evaluations and config codegen. For AI-driven experimentation work the MCP is the primary interface; the CLI fills in for CI integration and bulk operations the agent runtime is not the right place for.
Pairs with these skills
This integration pairs with the forthcoming experiment-design, experimentation-analytics skills. The skill landing pages and SKILL.md sources land in subsequent dispatches; cross-link hyperlinks are added when the skill pages ship.