pagespeed-insights-mcp
Identifies performance bottlenecks affecting user experience and SEO ranking without switching tools.
16-tool MCP server for the Google PageSpeed Insights and Chrome UX Report APIs. Lets Claude analyze, compare, and optimize web page performance — scores, Core Web Vitals, mobile vs desktop — without leaving the conversation.
- Ask Claude to analyze your website's performance score and get specific speed improvement recommendations.
- Generate a performance report comparing mobile and desktop metrics for your production site.
- Find the biggest performance bottlenecks affecting your web application's user experience metrics.
Identifies performance bottlenecks affecting user experience and SEO ranking without switching tools. Enables data-driven optimization decisions directly in Claude, reducing analysis overhead and improving page load metrics that impact conversion.
Engineering teams optimizing web applications for speed and frontend developers diagnosing performance regressions.
https://github.com/ruslanlap/pagespeed-insights-mcp
By ruslanlap
How to Get It
claude mcp add pagespeed-insights-mcp -- npx -y pagespeed-insights-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Analyze my website's performance score and get specific speed improvement recommendations
Trust Signals Auto-scanned
Data & Access
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 26 GitHub stars; contributors unknown; last commit 3d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 26 GitHub stars; contributors unknown; last commit 3d ago; license MIT.