Which integrations are available for this server?

Leverages Lighthouse audit data from the PageSpeed Insights API to surface performance scores, opportunities, and diagnostic issues (note: the PWA category was removed in Lighthouse 12+). Provides tools for analysing web page performance via the Google PageSpeed Insights API, including full scores, Core Web Vitals, opportunities, diagnostics, mobile vs desktop comparison, batch analysis, and per-category scores.

How do I use PageSpeed Insights MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@PageSpeed Insights MCP Server check Core Web Vitals for https://example.com on mobile" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

PageSpeed Insights MCP Server

by pravin157

Overview Schema Source Related Servers Discussions Admin

Python

Remote

PageSpeed Insights MCP Server

An MCP server that wraps the Google PageSpeed Insights API v5, exposing 7 focused tools for analysing web performance — scores, Core Web Vitals, opportunities, diagnostics, and batch analysis.

PWA Category Notice: The pwa Lighthouse category was removed in Lighthouse 12+ and is no longer available via the PSI API. Requesting it returns an API error. psi_check_pwa is intentionally not implemented.

Features

Tool	Description
`psi_analyze_url`	Full analysis — scores + CWV + top-5 opportunities
`psi_get_core_web_vitals`	Lightweight CrUX field data + lab CWV
`psi_get_opportunities`	Opportunities sorted by estimated savings
`psi_get_diagnostics`	Diagnostic issues (DOM size, JS work, etc.)
`psi_compare_mobile_desktop`	Side-by-side mobile vs desktop comparison
`psi_batch_analyze`	Analyse up to 10 URLs, partial-failure tolerant
`psi_get_category_score`	Single category score + audit breakdown

Related MCP server: MCP Server Pagespeed

Prerequisites

Python 3.11+
A Google API key with the PageSpeed Insights API enabled

Step 1 — Get a Google API Key

Go to the Google Cloud Console.
Create or select a project.
Navigate to APIs & Services → Library and search for "PageSpeed Insights API".
Click Enable.
Go to APIs & Services → Credentials → Create Credentials → API key.
Copy the generated key.

Quota: 25,000 requests/day · 400 requests/100 seconds per API key.
To request higher limits: Cloud Console → IAM & Admin → Quotas.

Step 2 — Install

With `pip` (virtualenv recommended)

cd page-speed-insights-mcp
python -m venv .venv

# Windows
.venv\Scripts\activate
# macOS/Linux
source .venv/bin/activate

pip install -r requirements.txt

With `uv` (recommended)

cd page-speed-insights-mcp
uv venv
uv pip install -r requirements.txt

Step 3 — Set `PSI_API_KEY`

Copy the example file and add your key:

cp .env.example .env

Edit .env:

PSI_API_KEY=AIzaSy...your_key_here

The server loads this automatically via python-dotenv. Alternatively, export it directly:

# Windows PowerShell
$env:PSI_API_KEY = "AIzaSy..."

# macOS/Linux
export PSI_API_KEY="AIzaSy..."

Security: Never commit your .env file or hardcode your API key in source code.

Step 4 — Verify the Installation

# Syntax check all modules
python -m py_compile pagespeed_mcp/server.py
python -m py_compile pagespeed_mcp/api.py
python -m py_compile pagespeed_mcp/models.py
python -m py_compile pagespeed_mcp/formatters.py
echo "All files compiled OK"

Step 5 — Register with Claude Desktop

Edit your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "pagespeed": {
      "command": "python",
      "args": ["-m", "pagespeed_mcp.server"],
      "cwd": "D:/SIVA/mcps/page-speed-insights-mcp",
      "env": {
        "PSI_API_KEY": "AIzaSy...your_key_here"
      }
    }
  }
}

Tip: Use the full path to the Python executable inside your virtualenv instead of bare python to avoid PATH issues:
Windows: "D:/SIVA/mcps/page-speed-insights-mcp/.venv/Scripts/python.exe"
macOS/Linux: "/path/to/page-speed-insights-mcp/.venv/bin/python"

Step 6 — Register with Claude Code

In your project's .claude/settings.json or ~/.claude/settings.json:

{
  "mcpServers": {
    "pagespeed": {
      "command": "python",
      "args": ["-m", "pagespeed_mcp.server"],
      "cwd": "D:/SIVA/mcps/page-speed-insights-mcp",
      "env": {
        "PSI_API_KEY": "AIzaSy...your_key_here"
      }
    }
  }
}

Or add via CLI:

claude mcp add pagespeed python -m pagespeed_mcp.server \
  --cwd "D:/SIVA/mcps/page-speed-insights-mcp" \
  --env PSI_API_KEY=AIzaSy...

Step 7 — Test with MCP Inspector

npx @modelcontextprotocol/inspector python -m pagespeed_mcp.server

This opens a browser UI where you can call each tool interactively.

Example Tool Calls

1. Full analysis (Markdown)

{
  "tool": "psi_analyze_url",
  "arguments": {
    "url": "https://web.dev",
    "strategy": "mobile",
    "categories": ["performance", "accessibility", "seo"]
  }
}

2. Quick Core Web Vitals check

{
  "tool": "psi_get_core_web_vitals",
  "arguments": {
    "url": "https://www.google.com",
    "strategy": "desktop"
  }
}

3. Opportunities with minimum savings

{
  "tool": "psi_get_opportunities",
  "arguments": {
    "url": "https://example.com",
    "strategy": "mobile",
    "min_savings_ms": 200
  }
}

4. Diagnostics

{
  "tool": "psi_get_diagnostics",
  "arguments": {
    "url": "https://example.com",
    "strategy": "mobile"
  }
}

5. Mobile vs Desktop comparison (JSON output)

{
  "tool": "psi_compare_mobile_desktop",
  "arguments": {
    "url": "https://web.dev",
    "response_format": "json"
  }
}

6. Batch analysis

{
  "tool": "psi_batch_analyze",
  "arguments": {
    "urls": [
      "https://web.dev",
      "https://www.google.com",
      "https://github.com"
    ],
    "strategy": "mobile",
    "categories": ["performance", "seo"]
  }
}

7. Single category score

{
  "tool": "psi_get_category_score",
  "arguments": {
    "url": "https://example.com",
    "category": "accessibility",
    "strategy": "desktop"
  }
}

Caching

Repeated calls for the same (url, strategy, categories) within a 5-minute window return cached results, avoiding unnecessary API quota consumption. The cache is in-memory and resets when the server restarts.

Rate Limits & Best Practices

Limit	Value
Requests per day	25,000
Requests per 100 seconds	400

Use psi_get_core_web_vitals for quick health checks (only fetches performance category).
In batch mode, specify only the categories you need to reduce response time.
The 5-minute cache prevents redundant calls in a single session.
On HTTP 429, the server automatically retries up to 3 times with back-off.

Project Structure

page-speed-insights-mcp/
├── pagespeed_mcp/
│   ├── __init__.py       # Package marker
│   ├── server.py         # FastMCP app + 7 tool definitions
│   ├── api.py            # HTTP client, cache, retry, error handling
│   ├── models.py         # Pydantic v2 input models
│   └── formatters.py     # Response extractors and Markdown/JSON renderers
├── requirements.txt
├── .env.example
└── README.md

Troubleshooting

Error	Fix
`❌ Missing API key`	Set `PSI_API_KEY` in `.env` or environment
`❌ API key rejected (HTTP 403)`	Verify the key is valid and PageSpeed Insights API is enabled in your Cloud project
`❌ Invalid URL (HTTP 400)`	Ensure the URL is publicly accessible and starts with `https://`
`⏳ Rate limited (HTTP 429)`	Reduce request frequency; the server retries automatically up to 3 times
`⏱️ Request timed out`	The page may be unreachable or very slow; try again
`pwa` category error	PWA category was removed from Lighthouse 12+ — do not pass `pwa`

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Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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PageSpeed Insights MCP Server

Features

Prerequisites

Step 1 — Get a Google API Key

Step 2 — Install

With pip (virtualenv recommended)

With uv (recommended)

Step 3 — Set PSI_API_KEY

Step 4 — Verify the Installation

Step 5 — Register with Claude Desktop

Step 6 — Register with Claude Code

Step 7 — Test with MCP Inspector

Example Tool Calls

1. Full analysis (Markdown)

2. Quick Core Web Vitals check

3. Opportunities with minimum savings

4. Diagnostics

5. Mobile vs Desktop comparison (JSON output)

6. Batch analysis

7. Single category score

Caching

Rate Limits & Best Practices

Project Structure

Troubleshooting

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

PageSpeed MCP Server

MCP Server Pagespeed

PageSpeed MCP Server

web-performance-mcp

With `pip` (virtualenv recommended)

With `uv` (recommended)

Step 3 — Set `PSI_API_KEY`