
considus/pagespeed-insights-mcp
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Local MCP server and CLI for Google PageSpeed Insights. Reports the median of several DISTINCT analyses with the spread, plus Chrome UX Report field data, so a change smaller than the noise is not...
Обзор
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. 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.
README
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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.
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.
| LCP | Verdict | |
|---|---|---|
| Lighthouse lab, mobile | 21.36 s | performance 27 / 100 |
| Real Chrome users, 28-day p75 | 1.20 s | FAST |
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
Установка
This server does not publish a one-line install command.
Open the repository installation guide Новичок в MCP? Начните с руководства на mcpskill.org →