Web Anatomy

MCP serverDev tools

Get better suggestions for improving your landing pages, backed by real examples instead of guesswork. Once added, your AI can review your page against a library of 3,500+ scored sections drawn from 500 real landing pages and recommend specific changes.

Use Web Anatomy in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Web Anatomy and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use Web Anatomy

Details

Available today. Use it from your connected AI after setup.

After adding it, share the landing page you want to work on and ask your AI to review it section by section. Use its suggestions to revise the page and ask again to check the improvements.

Web AnatomyStart free

What your AI can do with it

  • Compare your landing page sections against 3,500+ scored sections from real pages
  • Ground improvement suggestions in how 500 real landing pages are built
  • Recommend concrete changes to strengthen individual sections of your page
  • Point to real page examples when explaining what to adjust

Install Web Anatomy

The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user web-anatomy 'https://mcp.webanatomy.ai/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

    https://mcp.webanatomy.ai/mcp

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=web-anatomy&config=eyJ1cmwiOiJodHRwczovL21jcC53ZWJhbmF0b215LmFpL21jcCJ9

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://mcp.webanatomy.ai/mcp

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add web-anatomy --url 'https://mcp.webanatomy.ai/mcp'

    Run it once, then sign in with codex mcp login web-anatomy if the server asks for an account.

From the project's README

As published by gabrielamz/web-anatomy in README.md.

Skills for your AI agent that ship landing pages that work. Built from the plays the best SaaS companies actually shipped, grounded in a scored benchmark library so every recommendation cites a real page instead of generic advice.

$ npx skills add GabrielAmz/web-anatomy

Installs the Web Anatomy skill pack for Claude Code, OpenAI Codex, Cursor, Windsurf, and any agent that supports the Agent Skills spec.

What Web Anatomy is

Most AI agents rework a page from generic advice: add social proof, make the CTA stronger, tighten the headline. Web Anatomy gives the agent evidence instead. The skills read a page as a structure of known sections (hero, value proposition, trust, testimonial, pricing, FAQ, CTA), then ground every move in a benchmark library of real pages scored section by section.

The benchmark behind the skills (numbers to confirm before release):

  • 3,500+ scored sections
  • 500+ landing pages
  • 290+ companies

The skills run standalone with built-in patterns. Connecting the hosted MCP (highly recommended) pulls the live benchmark data and real reference screenshots into every report. See Live benchmark data.

The four altitudes

Web Anatomy works at four zoom levels. The altitude matches the question being asked.

AltitudeThe questionSkill
PageWhat do the strongest pages in this market do, and how does mine compare?find-examples
AuditHow does my whole page stack up, and what should I change first?audit-page
SectionHow do I level up one section, from foundational to best-in-class?research-best-practices
FixWrite the grounded copy to rework a page or build a new one.write-page

After the copy is written, build-page assembles the structure + copy into a shareable wireframe with a coherent, single-exemplar design system. It is the terminal step on both branches (improve and create), so it sits above the altitudes rather than inside one.

Run webanatomy-setup once first. It captures product, ICP, industry, competitors, and proof assets into .agents/webanatomy-context.md, so every skill gives sharper, on-brand recommendations.

Two flows

  • Improve an existing page: audit-page (diagnose) -> write-page (rewrite the weak sections) -> build-page (optional: assemble the improved page as a shareable wireframe, in your page's own look).
  • Create a new page: find-examples (pick one exemplar homepage) -> write-page build mode (a light outline adopts the exemplar's section order, then writes the copy) -> build-page (assemble the wireframe in the exemplar's look).

The skills

SkillAltitudeWhat it does
webanatomy-setupFoundationRun once. Captures product, ICP, industry, competitors, proof assets, and priority pages into .agents/webanatomy-context.md.
find-examplesPageThe market scan. Pulls the top-ranked pages and sections in a market, shows what to steal, and when you share your page, labels how it compares. Absorbs the old benchmark-compare.
audit-pageAuditScores the current page against a CRO rubric, diagnoses it section by section, and returns a prioritized fix list. Runs standalone, no MCP required.
research-best-practicesSectionThe section deep-dive. Takes one section and returns a tiered improvement ladder (foundational, competitive, best-in-class), each grounded in real benchmark sections.
write-pageFixThe copy engine. Turns a diagnosis, a tier, or a chosen structure into grounded copy-paste sections; reworks an existing page or writes a new one.
build-pageAssembleThe terminal assembler. Takes a structure + its copy and lays them out as a shareable wireframe with a single-exemplar design system (a benchmark page for a new page, your own page when improving).
moodboardPageThe section-by-section visual board. Captures the live page section by section and pulls benchmarks from the MCP, then composes each section as current-state-large + problems + a benchmark screenshot grid + discipline-tagged practices + recommendation. Where find-examples shows what to steal, moodboard composes the whole page as a visual reference you build from.

Visual Reports

Web Anatomy does not rely on chat to render screenshots. The output skills write local visual artifacts:

.webanatomy/
├── find-examples/
├── audit-page/
├── research-best-practices/
├── moodboard/
│   └── page-date/
│       ├── report.md
│       ├── report.html
│       └── references/
├── write-page/
│   └── topic-date/
│       ├── report.md
│       ├── report.html
│       └── references/
│           ├── current.png
│           └── company-section.png
└── build-page/
    └── page-date/
        ├── wireframe.html
        ├── design-system.md
        └── references/

The chat response should stay short: top findings, report path, and any screenshot or MCP limitations. report.html is the product experience.

Live benchmark data (optional, highly recommended)

The skills work on their own, so install them and start immediately. Connecting the hosted Web Anatomy MCP is never mandatory, but highly recommended: it grounds every recommendation in live benchmark data and real reference examples instead of static guidance, which is where the skills are at their best. It needs a beta token and one config command per IDE:

Sign in at https://www.webanatomy.ai/dashboard/mcp to get your token + per-IDE config. You must be signed in, because the page generates your personal token there.

The skills use MCP tools such as search_pages, get_page, search_sections, and get_section when connected, and degrade gracefully to static guidance when not. Scores, thresholds, raw marker coordinates, and benchmark field names stay internal; user-facing reports translate them into plain-English patterns and gap labels.

Want to see the benchmark first? Browse the public scored sections gallery at https://www.webanatomy.ai/best-landing-pages/sections — real landing-page sections, scored, with what makes each one work. It is the same library the MCP serves to your agent, so you can explore it before connecting anything.

Why "Anatomy"

Most AI-agent skill packs frame pages as a job (CRO, copywriting, SEO). Web Anatomy frames them as a structure: hero, proof, problem, solution, pricing, FAQ, CTA. Every section has known patterns, known anti-patterns, and known reference companies.

Every Web Anatomy skill turns a page into parts: hero, proof, problem, solution, pricing, FAQ, CTA. Each part has known patterns, anti-patterns, and benchmark examples. The framework and the evidence travel together.

Compatibility

  • ✅ Claude Code
  • ✅ OpenAI Codex
  • ✅ Cursor
  • ✅ Windsurf
  • ✅ Any agent that reads .agents/skills/<name>/SKILL.md per the Agent Skills spec

Install options

Option 1 — CLI (any agent):

# Installs the whole pack to .agents/skills/
npx skills add GabrielAmz/web-anatomy

# Update later (or just re-run the command above, it's idempotent)
npx skills update GabrielAmz/web-anatomy

Option 2 — Claude Code plugin (version-aware updates):

/plugin marketplace add GabrielAmz/web-anatomy
/plugin install web-anatomy

Claude Code knows the installed version and when a newer one ships. Update with /plugin marketplace update web-anatomy then /plugin update web-anatomy, or turn on auto-update for the marketplace to make it hands-off. Skills install namespaced: /web-anatomy:write-page, /web-anatomy:build-page, and so on.

Option 3 — clone and copy manually:

git clone https://github.com/GabrielAmz/web-anatomy
cp -r web-anatomy/skills/* .agents/skills/

After install, start with webanatomy-setup. The benchmark-backed workflows degrade gracefully when MCP isn't connected, falling back to static/reference guidance, but they are at their best with live benchmark data, so connecting MCP is highly recommended.

Repo layout

skills/ holds the skill pack, the source of truth installed by npx skills add.

Contributing

PRs welcome. See CONTRIBUTING.md for the new-skill recipe: kebab-case, YAML front matter, clear workflow names, and body under 5K tokens.

License

MIT. Use it, fork it, sell it, ship it.


Built by Gabriel Amzallag. The Web Anatomy pack is a public extraction of the patterns powering a private landing-page benchmark and audit tool. The skills give you the framework; the analyzer gives you the data.

Signals

GitHub stars
11
Last commit
Jul 2026
Advanced
Delivery
webanatomy MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
ai-webanatomy-webanatomy
Source
github.com/gabrielamz/web-anatomy
Hosted endpoint
https://mcp.webanatomy.ai/mcp