Performance Analysis MCP Server
Provides capabilities for auditing web page performance using Google Lighthouse, including collecting performance metrics and generating reports.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Performance Analysis MCP Servercheck page performance for https://www.lowes.com"
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.
Performance Analysis MCP Server
Lightweight MCP server for collecting page performance metrics (Playwright + CDP + Lighthouse) and returning a normalized PerformanceReport.
Prerequisites
Node.js (16+ recommended)
npm
Optional: network access to target URLs
Related MCP server: LightScout MCP
Install
npm install
# Install Playwright browsers (required for collectors)
npx playwright installBuild / Type-check / Test
npm run build
npm run lint
npm testRun as MCP Server
The default command starts an MCP stdio server with an analyze_page tool.
npm startThe MCP tool accepts:
{ "url": "https://example.com" }It returns a human-readable summary plus structured PerformanceReport content.
Run HTTP Compatibility Server
The HTTP server is available for local testing and non-MCP clients. You can provide a default URL via DEFAULT_URL or pass a URL in each request.
npm run start:httpWith a default URL:
DEFAULT_URL=https://example.com npx ts-node src/index.ts http --no-promptServer API
GET /health→ returns{ ok: true }POST /analyzewith JSON{ "url": "https://..." }→ returns analysis JSON plussummarystring.
Example using curl (returns JSON file):
curl -s -X POST http://localhost:3333/analyze \
-H "Content-Type: application/json" \
-d '{"url":"https://www.lowes.com"}' -o report.jsonOne-off analyze (CLI)
npx ts-node src/index.ts analyze https://www.lowes.com > report.jsonThe CLI prints JSON followed by a human-readable summary.
Files of interest
src/schema/performance-report.ts— canonical schema and validatorsrc/collectors/playwright.ts— Playwright collectorsrc/collectors/cdp.ts— CDP network capture helpersrc/tools/analyze-page.ts— orchestrates collectors and adapts resultssrc/tools/lighthouse.ts— Lighthouse runner (Phase 2)src/tools/format-report.ts— text formatter for human-friendly outputsrc/server/mcp.ts— MCP stdio server andanalyze_pagetoolsrc/server/http.ts— HTTP compatibility server
Troubleshooting
If Playwright complains about missing browsers, run
npx playwright install.If
tscnot found, runnpm installto install devDependencies.
Next steps
Add automated recommendations, persistence, or LLM analysis integration.
Available Tools
1 toolanalyze_pageAnalyze Page PerformanceARead-only
Collect page performance metrics for a public http(s) URL using Playwright and CDP.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Absolute public http(s) URL to analyze |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true. Description adds that it uses Playwright and CDP, implying a browser launch and network dependency, which is useful context. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence, front-loaded with action and resource. No extraneous information. Score slightly reduced because it could be grammatically tighter ('Collect' vs 'Collects').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of one parameter, no output schema, and good annotations, the description is fairly complete. It explains what the tool does and its input. Could mention what metrics are collected or typical output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single parameter 'url' has full schema coverage (100%) with clear description. The tool description does not add new semantics beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Collect' and resource 'page performance metrics', clearly indicating the tool's function. It specifies the scope 'public http(s) URL' and mentions technology 'Playwright and CDP', leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explicitly states the tool works with 'public http(s) URL', guiding when to use. No alternatives given, but with no sibling tools, this is sufficient. Could be slightly enhanced with explicit scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of confusion between tools; the purpose is singular and clear.
The single tool follows a consistent verb_noun pattern (analyze_page), which is clear and predictable.
The server claims to be a Performance Analysis MCP Server but provides only one tool, which is too few for the implied broader scope. A single tool feels thin and under-scoped.
The server covers only basic page performance metrics. Missing tools for audits, comparisons, history, or reporting create significant gaps for a performance analysis server.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Website performance monitoring: scans, Core Web Vitals, RUM data and alerts.
Core Web Vitals metrics by CMS, CDN, and framework — free remote MCP, no auth.
Validate HTML/CSS, audit SEO and JSON-LD, check links, and capture responsive screenshots.
Scan a web page for accessibility, security, privacy, quality and SEO issues, with fixes.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI models to perform Google Lighthouse website performance analysis, including Core Web Vitals, accessibility, SEO audits, and actionable optimization recommendations. Provides comprehensive web performance insights through natural language interactions.1,3543MIT
- AlicenseAqualityDmaintenanceCore Web Vitals analysis powered by Lighthouse. Four tools: analyze a URL, compare two URLs, check against thresholds, or crawl an entire site. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible AI tool.420MIT
- AlicenseNot gradedqualityBmaintenanceReal-machine, real-browser web perf measurement with ~99% iframe coverage. LLM-native + AI-agent-loop ready.2Apache 2.0
- AlicenseBqualityDmaintenanceEnables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.514MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Sindhura30/pageperformance-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server