PageSpeed Insights MCP server

PageSpeed Insights MCP

Measures a web page with Google PageSpeed Insights and reports the median of several runs with the spread beside it, so a number arrives with its uncertainty. Works from an assistant that speaks MCP, or from a terminal.

Standard library only. No virtual environment, no pip, no compiled dependency. Clone it and run it.

Docs · Install · FAQ

Why another one

There are already several PageSpeed MCP servers. As far as we can tell, every one of them only runs Lighthouse once and hands the model the number.

A single Lighthouse run is noise. Total Blocking Time routinely swings threefold between runs on a page that has not changed, and the headline performance score is a weighted blend that inherits every bit of that. Ask once and you get a figure with no error bars, and no way to tell a real regression from the instrument moving. That is not a small imprecision, it is the difference between measuring something and guessing at it confidently.

There is a second problem underneath, and it is worse because it is invisible. PageSpeed caches its result per URL and replays it. Ask five times and you can be handed one analysis five times, which quietly turns a median into a vote for whatever Google happened to have cached. Minutes after a deploy on 30 July 2026 that is exactly what happened here, 2 of 3 runs came back with a byte-identical timestamp from before the deploy, dragging the average back to the pre-fix score while the one fresh run showed the fix working. A tool that reports one run would have reported the stale number as current, with nothing to indicate anything was wrong.

This one takes the median of 5 runs by default, prints the min-max spread next to every figure, drops runs that were cached replays, and tells you how many it dropped.

The lab is not your users

Both of these are true, measured on the same page on the same afternoon.

That is the BBC home page. The lab says the site is catastrophically slow. Real people are getting it in 1.2 seconds.

Neither number is wrong, they answer different questions. Lighthouse is a simulation on throttled hardware, useful because it is repeatable and you can run it against a page nobody has visited yet. Field data is what actually happened to real Chrome users, and it is the only thing Google ranks on. A tool that shows you one and not the other is misleading you, whichever one it picks.

So this reports both, separately, and never merges them into a single figure.

What it does

and metric.

• Median of N distinct analyses, with the min-max spread beside every score

re-analyses a URL about once a minute and replays the cached result to everything that asks in between. Five requests in a row is one measurement five times over.

• Keeps asking until it has N genuinely different analyses, because Google

rather than padding the count when time runs out.

• Says what that cost in calls and seconds, and reports fewer analyses honestly

weekly history, when Google has it.

• Real-user data from the Chrome UX Report, current and up to 6 months of

for evidence about real visitors.

• Says plainly when Google has none, rather than letting a lab score stand in

apart from both.

• Tells an exhausted quota apart from a broken page, and a misconfigured key

Things to actually ask it

Four that exercise different parts of it, and none need you to know a tool name.

Shortened. The full README is on GitHub.