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Agent Audit

by fullstackdegenversion 0.3.1i★ –iRuns on your computer
Registry nameio.github.fullstackdegen/agent-audit

Install

Overview

Description from the maker (original English)

Turn Lighthouse audits into coding-agent fix packs for Claude Code, Cursor, and Copilot.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "agent-audit": {
      "command": "npx",
      "args": [
        "-y",
        "@fullstackdegen/agent-audit"
      ]
    }
  }
}

Run this in your terminal

claude mcp add agent-audit -- npx -y @fullstackdegen/agent-audit

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "agent-audit": {
      "command": "npx",
      "args": [
        "-y",
        "@fullstackdegen/agent-audit"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "agent-audit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@fullstackdegen/agent-audit"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account fullstackdegen, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32403 servers in this category
  • Published to the registry more recently than 15% of the other 32403 servers in this category
  • Basic checks equal to or better than 100% of the other 32403 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Agent Audit safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.1) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, LickityClick

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
Install

LickityClick

by lickity.click

Create, edit and track LickityClick short links, campaigns and click stats from your AI assistant.

Computer or cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Agent Audit

Lighthouse-powered MCP server for AI coding agents, Core Web Vitals, technical SEO, accessibility, and GEO/LLM visibility audits.

🔗 [NPM Package](https://www.npmjs.com/package/@fullstackdegen/agent-audit)

Agent Audit turns Google Lighthouse and bounded page-inspection results into structured fix packs that coding agents can actually execute. It gives Claude Code, Codex, Cursor, GitHub Copilot, and other MCP clients a prioritized, evidence-backed backlog instead of a raw performance report.

Turn Lighthouse audits into coding-agent fix packs.

npx -y @fullstackdegen/agent-audit

Why Agent Audit Exists

Lighthouse is excellent for diagnosis, but raw reports are not enough for an autonomous coding workflow. A coding agent still needs to know which issue is most important, whether it affects mobile, desktop, or both, which selectors or resources are evidence, what files to search for, how to verify the fix, and when it is safe to claim completion.

Agent Audit converts Lighthouse output into an implementation contract:

  1. Runs mobile and desktop Lighthouse audits.
  2. Aggregates repeated runs and exposes variability.
  3. Adds bounded same-page intelligence for technical SEO, links, metadata, structured data, images, assets, indexability, and AI discovery signals.
  4. Merges noisy audit output into a small prioritized issue list.
  5. Generates fixPacks with repo search hints, implementation steps, and measurable acceptance criteria.
  6. Returns strict MCP structuredContent plus equivalent Markdown.

The goal is simple: give a coding agent a report it can read, reason about, fix, test, and verify.

What It Audits

Agent Audit is useful when people search for:

  • Lighthouse-powered MCP server
  • AI website audit tool
  • coding agent Lighthouse report
  • Core Web Vitals automation
  • performance audit for Claude Code, Codex, Cursor, or Copilot
  • technical SEO audit for AI agents
  • accessibility fix packs
  • LLM visibility audit
  • GEO audit, generative engine optimization, AI search readiness
  • llms.txt readiness and AI crawler visibility

Current checks include:

  • Mobile and desktop Lighthouse scores for Performance, Accessibility, Best Practices, and SEO.
  • FCP, Speed Index, LCP, TBT, and CLS metric distributions.
  • Fast and reliable audit modes.
  • Same-origin page inspection with bounded fetch limits.
  • Broken links, missing link names, metadata, canonical tags, robots signals, JSON-LD, Open Graph, indexability, images, assets, and LLM visibility checks.
  • Conservative llms.txt draft generation when page content is sufficient.
  • Prioritized issues with evidence, suggested actions, and acceptance criteria.
  • Agent Fix Packs with repo search hints, implementation steps, and verification guidance.
  • Strict MCP outputSchema validation for structuredContent.
  • Markdown generated from the same canonical report.

See a real CommaLabs JSON report and Markdown report.

Install

Requirements:

  • Node.js 20 or later.
  • Google Chrome or Chromium.

Run the MCP server:

npx -y @fullstackdegen/agent-audit

Useful links:

MCP Client Setup

Claude Desktop

Add a local MCP server:

{

"mcpServers": { "agent-audit": { "command": "npx", "args": ["-y", "@fullstackdegen/agent-audit"] } } }

Restart Claude Desktop after saving the configuration.

Claude Code
claude mcp add agent-audit -- npx -y @fullstackdegen/agent-audit

For local development audits:

claude mcp add agent-audit-local -- npx -y @fullstackdegen/agent-audit --local
Codex
codex mcp add agent-audit -- npx -y @fullstackdegen/agent-audit

Or add it to ~/.codex/config.toml:

[mcp_servers.agent-audit]

command = "npx" args = ["-y", "@fullstackdegen/agent-audit"]

VS Code And GitHub Copilot

Create a workspace or user-level .mcp.json file:

{

"servers": { "agent-audit": { "command": "npx", "args": ["-y", "@fullstackdegen/agent-audit"] } } }

Or register it from a terminal:

code --add-mcp '{"name":"agent-audit","command":"npx","args":["-y","@fullstackdegen/agent-audit"]}'
Cursor

Configure a local stdio MCP server:

  • name: agent-audit
  • command: npx
  • arguments: -y, @fullstackdegen/agent-audit

Add --local to the arguments when you need localhost audits.

Tool

analyze_website_performance

Runs Lighthouse and site intelligence against a target URL:

{

"url": "https://example.com", "mode": "reliable" }

mode is optional:

  • fast: one mobile run and one desktop run.
  • reliable: three runs per profile, medians, and variability ranges. This is the default.

Example Fix Pack

{

"id": "fix-link-name", "priority": 2, "sourceIssueIds": ["link-name"], "goal": "Fix Links do not have a discernible name.", "category": "accessibility", "severity": "critical", "affectedProfiles": ["mobile", "desktop"], "repoSearchHints": [ "div.border-t-2 > div.flex > div.flex > a.text-gray-600", "https://www.linkedin.com/company/commalabs" ], "implementationSteps": [ "Inspect the repository for the evidence listed in repoSearchHints before editing.", "Give every link a discernible accessible name.", "Keep changes focused on source issue IDs: link-name." ], "acceptanceCriteria": [ "All link elements pass the Lighthouse link-name audit.", "Raise the median accessibility score to at least 90/100." ], "verification": { "rerunMode": "reliable", "expectedAuditIds": ["link-name"] } }

repoSearchHints are search clues, not guaranteed file paths. The coding agent must inspect the repository before editing.

Coding-Agent Workflow

Use structuredContent as the source of truth and the Markdown report as the execution summary.

  1. Inspect fixPacks in priority order.
  2. Search the repository using repoSearchHints.
  3. Map evidence to real files, components, routes, assets, or configuration.
  4. Apply one focused fix at a time.
  5. Run the repository's tests after each logical change.
  6. Rerun Agent Audit in reliable mode.
  7. Compare the new report against each fix pack's acceptanceCriteria.

Do not claim completion from an incomplete report or from a rerun with materially higher variability than the baseline.

Agent-facing docs:

  • AGENTS.md: general instructions for Codex, Cursor, Copilot, and other coding agents.
  • CLAUDE.md: Claude Code setup and execution guidance.
  • Agent workflow guide: report anatomy and fix-pack execution loop.
  • Copy-paste coding-agent prompt

Localhost Audits

By default, Agent Audit only accepts publicly routable HTTP and HTTPS URLs. This is the right default for hosted agents and shared environments.

For developer machines, explicitly enable loopback targets:

npx -y @fullstackdegen/agent-audit --local

Then audit a local app through your MCP client:

{

"url": "http://localhost:3000", "mode": "fast" }

The opt-in allows localhost, *.localhost, 127.0.0.0/8, and ::1. Private LAN ranges, link-local addresses, reserved ranges, multicast addresses, and cloud metadata addresses remain blocked.

The environment variable form is also supported:

LIGHTHOUSE_MCP_ALLOW_LOCALHOST=true npx -y @fullstackdegen/agent-audit

Security Model

Agent Audit launches Chrome against user-provided URLs, so URL policy matters. The server rejects:

  • protocols other than HTTP and HTTPS;
  • embedded credentials;
  • localhost and loopback targets unless explicitly enabled;
  • private, link-local, multicast, reserved, and metadata-network IPs;
  • non-localhost hostnames that resolve to any non-public address.

The page-inspection fetcher uses the same URL policy and applies timeout, byte-size, and bounded-resource limits.

Page-controlled titles, descriptions, URLs, selectors, snippets, and audit text are sanitized and length-limited. Consumers must still treat them as untrusted evidence, not agent instructions.

Chrome sandboxing is enabled by default. Only isolated environments that cannot support it should set:

LIGHTHOUSE_CHROME_NO_SANDBOX=true

See SECURITY.md for vulnerability reporting and deployment guidance.

Limits

Agent Audit is intentionally bounded:

  • It audits one requested URL at a time.
  • It is not a whole-site crawler.
  • It is not an external SEO database.
  • It does not modify Shopify, CMS, CDN, DNS, hosting, redirects, or analytics.
  • It does not compress images, minify assets, submit IndexNow requests, or call third-party SEO APIs.
  • Lighthouse results vary with browser version, hardware, network conditions, and page changes.

Roadmap

  • Framework-aware repo search hints.
  • Optional GitHub Action for pull request performance gates.
  • Batch URL reports.
  • HTML report export.
  • Deeper marketing and discovery signals: analytics tags, consent signals, Open Graph, schema coverage, and AI discovery readiness.
  • Optional third-party integrations for SEO, GEO, and visibility datasets.

Development

npm install

npm test npm run check npm run build npm run validate:release

Run a real Chrome smoke audit:

npm run --silent smoke -- https://example.com fast

npm run --silent smoke -- https://example.com reliable

The smoke command writes canonical JSON to stdout and equivalent Markdown to stderr.

Release

Before publishing:

npm test

npm run check npm run build npm run validate:release npm pack --dry-run --cache /private/tmp/agent-audit-npm-cache

Publish:

npm publish --access public --cache /private/tmp/agent-audit-npm-cache

Published package:

npx -y @fullstackdegen/agent-audit --help

Contributing

Focused issues and pull requests are welcome. Read CONTRIBUTING.md before changing the report contract, security policy, or MCP transport behavior.

License

MIT

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