MCP, or Model Context Protocol, is an open standard that lets AI tools connect to external services. UserTesting’s MCP server helps supported tools recruit participants, create studies, and launch tests from inside the AI workflow.

Yes. UserTesting follows enterprise-grade security practices, including secure authentication and workspace-level controls. Customer data is not used to train third-party AI models.

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Bring UserTesting into your AI workflow

Q: Which tools does UserTesting support through MCP?

UserTesting supports Claude, ChatGPT, Figma Make, and other applications that support MCP.

Q: What can teams do with UserTesting’s MCP server today?

Today, teams can recruit participants, create studies, and launch tests from MCP clients. More ways to surface customer insight across workflows will continue to expand.

Q: How does participant recruiting work?

Recruiting is powered through UserTesting and User Interviews, helping teams define target audiences and recruit the right participants as part of the same study-creation flow.

Use UserTesting’s MCP server to recruit participants, create studies, and launch tests from Claude, ChatGPT, Figma Make, and other MCP clients.

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Limited early access available.

Give AI real human context

UX researchers can move from analysis to action faster. Designers can generate with better context and validate when concepts are ready. UserTesting brings customer understanding into the tools teams already use.

Analyze with customer insight in one place

Bring UserTesting, analytics, and AI tools together in a single workflow, making it easy to compare signals and customer feedback, and move seamlessly from insights to action—all without switching platforms.

Generate better design directions from the start

Integrate real customer context into Figma Make and MCP clients, empowering teams to solve real user needs with relevant, impactful solutions built on insight—not assumption.

Validate AI outputs without breaking flow

Recruit the right people, launch tests, and bring results back into the same AI workflow—so teams can validate AI-generated outputs with real people.

Built for MCP clients

Works with Claude, ChatGPT, Figma Make, and other MCP clients to recruit participants, create studies, and launch tests—bringing customer insight into the tools where work happens.

See UserTesting’s MCP server in action

If your team uses Claude, ChatGPT, Figma Make, or another MCP clients to analyze data, generate concepts, or make product decisions, we’ll show you how UserTesting fits directly into that workflow.

Early access is currently limited to select teams.

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FAQ

What is MCP?

Which tools does UserTesting support through MCP?

What can teams do with UserTesting’s MCP server today?

How does participant recruiting work?

Is my data secure?

Top Recruiting Features

How teams use MCP

For insight seekers: from signal to decision in one session

With UserTesting connected via MCP, teams can bring behavioral data and UserTesting qualitative insight into the same Claude or ChatGPT session. Ask why checkout abandonment is rising and get an answer that draws on web analytics funnel data and UserTesting verbatims together — so the brief that comes out of it is sharper, more defensible, and visible to the people making decisions in real time.

Learn how to make defensible design decisions with AI. Boost confidence, balance speed, and keep human insight at the center of product design.

For builders and creators: generate fast, build right

When you prompt Figma Make or Claude without customer context, the model only knows patterns — not how your specific users actually think or abandon. MCP loads real customer insight before it generates anything, so the first direction is more accurate. And when you've already built something fast and need to validate it, UserTesting is right there — no separate tool, no broken flow.

Synthetic research vs human insight: what CMOs need

For teams: from insight to decision, in one flow

Study creation and recruiting through User Interviews happen alongside each other — inside Claude, ChatGPT, or Figma Make. Insights surface in Slack and AI assistants where the rest of the team already is, so decisions get made with real customer understanding — not because insights got louder, but because it got closer to where decisions happen.