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WebAnatomy logo
Health: ActiveRecent health check succeeded.Last checked 10/12/2026, 5:46:41 AM

WebAnatomy

User RatingsBe the first to rate and review this MCP server!
View Repository11 GitHub StarsTotal stargazers on GitHub for the source repository (11 stars).Visit Website
landing-pagesbenchmarkingcopywritingcromcp

Grounds landing-page audits, research, copy, and wireframes in scored examples from real SaaS pages.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ā–¾

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "webanatomy": {
      "url": "https://www.webanatomy.ai/dashboard/mcp"
    }
  }
}

šŸ’” Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesšŸ’» More in Developer Tools

Overview

The WebAnatomy MCP server connects AI agents to a hosted benchmark of scored landing pages and sections. Its tools include search_pages, get_page, search_sections, and get_section, which provide live reference data and screenshots for landing-page work. Use it when an agent needs evidence-based recommendations for auditing, researching, or rewriting a page rather than static guidance. The MCP connection is optional, and the accompanying skills fall back to built-in patterns when it is unavailable.

Use cases

•Audit an existing landing page against a CRO rubric
•Find benchmark pages for a target market
•Research improvement patterns for one page section
•Write grounded replacement landing-page copy
•Assemble revised copy into a shareable wireframe

Key features

•Searches scored benchmark pages
•Retrieves page and section benchmark data
•Provides real reference screenshots
•Supports page audits and section research
•Generates grounded landing-page copy
•Produces HTML reports and wireframes

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by WebAnatomy.

Extracted Tool Capabilities
Searches scored benchmark pages
Retrieves page and section benchmark data
Provides real reference screenshots
Supports page audits and section research
Generates grounded landing-page copy
Produces HTML reports and wireframes

How WebAnatomy works

What the WebAnatomy MCP server does

The WebAnatomy MCP server gives landing-page workflows access to a benchmark of more than 3,500 scored sections across more than 500 pages and 290 companies, according to the repository. It is intended for agents working on SaaS and other product landing pages that need concrete references instead of broad conversion advice.

The underlying framework treats a page as a set of recognizable sections, including the hero, value proposition, trust elements, testimonials, pricing, FAQ, and CTA. Agents can use the benchmark to compare pages, investigate a specific section, identify gaps, and produce revised copy. The related skill pack also creates local reports and wireframes for these workflows.

How it works

The hosted MCP exposes benchmark searches and page or section lookups. The documented tools are search_pages, get_page, search_sections, and get_section. Connected skills use these results to bring current benchmark data and reference screenshots into their reports. Internal scores, thresholds, marker coordinates, and field names are translated into plain-language findings rather than exposed directly in user-facing output.

The repository describes four main working levels: finding example pages, auditing a complete page, researching one section, and writing replacement copy. A separate build step assembles structure and copy into a shareable wireframe. The moodboard workflow captures a page section by section and combines the current page, issues, benchmark screenshots, practices, and recommendations.

Setup and configuration

Install the skill pack with npx skills add GabrielAmz/web-anatomy, or install it as a Claude Code plugin, or clone the repository and copy its skills into .agents/skills/. Run webanatomy-setup after installation to record product details, target customers, industry, competitors, proof assets, and priority pages in .agents/webanatomy-context.md.

To use live benchmark data, sign in to the Web Anatomy dashboard and obtain a beta token. The repository provides a per-IDE configuration command from that dashboard rather than documenting a fixed environment-variable name. The MCP connection is optional; the skills can run without it using static and built-in reference guidance.

Tools and capabilities

The WebAnatomy MCP server supports:

  • Searching benchmark pages and retrieving individual page records.
  • Searching scored landing-page sections and retrieving section details.
  • Supplying real reference examples and screenshots to agent reports.
  • Supporting page comparison, full-page audits, section research, and grounded copywriting.

The skill pack writes artifacts beneath .webanatomy/, including Markdown and HTML reports, reference images, wireframes, and design-system notes. build-page uses a single exemplar design system when assembling a new or improved page.

Limitations and notes

Live benchmark access requires a beta token and sign-in through the Web Anatomy dashboard. Without the MCP connection, the skills remain usable but rely on static guidance and built-in patterns, so they do not provide the live benchmark results or reference retrieval described above.

The repository presents Web Anatomy primarily as an Agent Skills pack with an optional hosted MCP connection. It names Claude Code, OpenAI Codex, Cursor, and Windsurf as supported environments, along with agents that implement the Agent Skills specification. The documented material does not specify a fixed MCP transport or a named environment variable for configuration.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
11
Stargazers on the source repository.
Last commit
3mo ago
Most recent push to the default branch.

Reviews

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Frequently Asked Questions about WebAnatomy

WebAnatomy is an MCP server that connects AI agents to a hosted benchmark of scored landing pages and sections. Its main tools are search_pages, get_page, search_sections, and get_section, which provide live benchmark data and reference screenshots for page audits, section research, comparisons, and evidence-based landing-page copy.

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Technical Specs & Signals

CategoryšŸ’»Developer Tools
More technical detailsExpand ā–¾
TransportSSE (Remote)
LicenseMIT
ClientsClaude Code, OpenAI Codex CLI, Cursor, Windsurf
Last updatedOct 6, 2026
15/15 checks healthy over the last 63d
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars11
GitHub Star CountTotal stargazers on GitHub representing community popularity (11 stars).
Last commit3mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 2, 2026
39Quality signal: Fair Ā· 39/100How this signal is calculated ā–¾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 8/30/2026 via OSV.dev Ā· https://www.webanatomy.ai/dashboard/mcp (npm)

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