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Access session replays, funnels, errors, and performance diagnostics to improve UX.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Webeyez MCP" MCP server from askskill: Run: claude mcp add 'io-github-webeyez-analytics-webeyez-mcp-server' -- npx -y @webeyez/mcp-server
Use Webeyez MCP to analyze this week's signup funnel, identify the step with the highest drop-off, and review related session replays to summarize 3 likely causes.
Returns the main funnel drop-off points, replay-based observations, and a summary of likely conversion blockers.
Using Webeyez MCP, find the most frequent errors on the checkout page in the last 7 days, rank them by affected users, and note whether they correlate with specific devices or browsers.
Outputs a ranked error list, impact scope, device or browser distribution, and repair priorities.
Use Webeyez MCP to inspect performance diagnostics for the product detail page, identify the main slow-loading metrics, and explain through session replays how these issues affect user behavior.
Provides abnormal performance metrics, the affected parts of the experience, and replay-based evidence of user impact.
No documentation provided
Check the source repo for usage and examples.
Expose website JavaScript functions as MCP tools for AI browser interaction.
Automate browsers to capture page data, logs, and network insights for testing.
Automate browser tasks, capture console logs, and take screenshots for web workflows.
Analyze webpages accurately by combining DOM structure with visual context.
Analyze website performance and diagnose optimization issues with PageSpeed and Chrome UX data.
Let AI browse via your real Chrome for extraction and multi-step workflows.