How to Use the Hotjar (Behavior Analytics) MCP in Windsurf

Q: Can Windsurf read my Hotjar (Behavior Analytics) session recordings?

Yes. Cascade uses the listrecordings tool to fetch session metadata. It looks at duration, click counts, and drop-off points to figure out where users struggle with your current codebase.

Connect Hotjar (Behavior Analytics) to Windsurf and let Cascade autonomously query UX metrics and survey data right in your IDE.

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Connect Hotjar (Behavior Analytics) MCP to Windsurf

Create your Vinkius account to connect Hotjar (Behavior Analytics) to Windsurf and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Hotjar (Behavior Analytics) with Windsurf

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Claude

Perplexity

Let Cascade map your funnels

This MCP Server connects Windsurf directly to your Hotjar workspace to run `list_funnels` and `list_sites`. You ask Cascade why users abandon the checkout flow, and it immediately finds the target project before pulling the drop-off metrics. Instead of making you dig through dashboards, Cascade chains these requests automatically. It cross-references the funnel data with `list_recordings` to identify specific sessions where users got stuck, giving you raw behavioral context without leaving your editor.

Analyze feedback inside Windsurf

Your agent uses `list_surveys` and `list_survey_responses` to pull qualitative user sentiment straight into your local workspace. When a product manager flags a bug report, Cascade grabs the exact survey context to help you reproduce the issue. You don't have to manually export CSVs anymore. The agent matches `list_feedback` entries with current site parameters from `get_site`, allowing it to suggest code fixes based on actual user complaints.

Autonomous heatmap investigations

Cascade queries `list_heatmaps` and `get_heatmap` to see exactly where users click on your live components. If you suspect a button is invisible to users, your AI client fetches the coordinate data to prove it. This changes how you iterate on UI design. The agent reads the click density, notices that users are clicking unlinked text instead of the primary CTA, and drafts a PR to fix the visual hierarchy immediately.

Setup guide

Set up Hotjar (Behavior Analytics) MCP in Windsurf

Prerequisites

Windsurf IDE installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.
2

Add the Hotjar (Behavior Analytics) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Refresh MCPs

Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.
4

Verify in Cascade

Start a new Cascade conversation and ask something like "Show my Hotjar (Behavior Analytics) payment history." If connected, Cascade will call the Hotjar (Behavior Analytics) tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json

{
  "mcpServers": {
    "hotjar-behavior-analytics-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about Hotjar (Behavior Analytics) MCP in Windsurf

Open Settings, navigate to Cascade, and find the MCP Servers UI. You can either use the built-in marketplace for a one-click install or edit your mcp_config.json file directly. Click refresh, and Cascade will auto-discover the tracking tools.

Yes. Cascade uses the `list_recordings` tool to fetch session metadata. It looks at duration, click counts, and drop-off points to figure out where users struggle with your current codebase.

Not at all. The standard runs these queries entirely out of band. Your editor stays fast while the agent waits on the API responses from `get_heatmap` or `get_survey`.

You define a high-level goal like finding out why the pricing page converts poorly. Cascade autonomously runs `list_funnels` to find the drop-off, then triggers `list_feedback` to read what users actually said about the pricing.

The integration only reads what your API token allows. When pulling data through `list_recordings` or `list_survey_responses`, it processes raw analytics strings and metadata, relying on your existing Hotjar masking settings to keep PII out of the prompt window.

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