MCP.Market

LanceRoylo MCP server

by LanceRoylo·io.github.LanceRoylo/mcp·v0.1.2

AEO scoring, llms.txt audit, and agent-readiness checks for AI agents.

A92/100grade A
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A92/100

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LanceRoylo tools (3)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • aeo_scan

    Score a website's Answer Engine Optimization (AEO) readiness from 0 to 100. Returns the score, letter grade, schema coverage breakdown, technical signals (og:image, h1 count, canonical, etc.), and red flags. Use this when you want to know how citable a site is to ChatGPT, Claude, Perplexity, Gemini, Microsoft Copilot, and Google AI Overviews. Methodology at neverranked.com/standards/methodology.

  • agent_readiness_check

    Audit a website for AI agent task-surface readiness. Looks for Schema.org Action types (ReserveAction, ApplyAction, BuyAction, OrderAction, ContactAction) in JSON-LD blocks. Returns a 0-100 score with vertical-specific baselines and validation issues. Use this when you want to know if a site is prepared for the agentic AI shift, where AI agents perform tasks (book, apply, buy) on behalf of users r

  • llms_txt_check

    Audit a website's /llms.txt file against the published standard. Returns a 0-100 score, grade, presence of required structural elements (H1, blockquote, sections), link health, and freshness. Use this when you want to know if a site is properly exposing its content map to AI engines that respect llms.txt (Anthropic Claude, with OpenAI and others stated to follow). Standard at neverranked.com/stand

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan11 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 0 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 92/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How LanceRoylo compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
92/100
higher than 90% of 4,460 AI and agents servers
Tools
3
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break

What its tools let an agent do: 3 read

Install LanceRoylo in Claude Code, Cursor or VS Code

Runs npx -y @neverranked/mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add mcp -- npx -y @neverranked/mcp
Add to Cursor

What the publisher says

From the LanceRoylo repository's README, as published. We do not edit it. Read it on GitHub

Never Ranked

NeverRanked is a research engagement that measures what AI answer engines cite for a category. The output is a forensic memo plus a prepped punch list for the customer's team to execute against.

This repository holds the marketing site, the dashboard worker source (under dashboard/), and the historical artifacts from the company's prior product.

What this company was, and what it is now

Until May 2026, NeverRanked sold a JavaScript snippet that was claimed to drive AI citations. We ran a pre-registered kill test against our own domain. The result was zero citations. The LLM crawlers do not execute JavaScript, so the snippet was structurally invisible to them.

We stopped selling that product, retracted the public content that promoted it, and rebuilt the company around the measurement layer that does work.

This repository contains both states: the current honest surfaces (homepage, About, ASB pitch, terms, privacy, llms.txt) and the historical artifacts (retired blog posts, retired case studies, retired audits, retired explainers). Anything that contradicts the retraction is either replaced with an honest holder or marked as retired in place.

For the current state of every code path, see ~/.claude/projects/-Users-lanceroylo-Desktop-neverranked/memory/coderewritestatus_2026-05-21.md in Lance's local Claude memory.

What we measure now

Seven measured surfaces, every day. Six AI tools plus a control.

cite their sources: Perplexity, ChatGPT search, Gemini grounded, Google AI Overviews.

  • Four citation-grade engines that search the live web and

data: Claude, Gemma.

  • Two model-knowledge engines that answer purely from training

It does not cite or answer, it returns, and it runs beside the others so a move can be separated from noise.

  • One classic-search control, Bing organic top-5. Not an AI tool.

Both layers measure different failure modes. A brand invisible in citation is invisible when AI fact-checks itself. A brand invisible in model knowledge is invisible at the baseline, before any search happens.

What we deliver

A forensic memo plus a prepped punch list. Per query, per engine, per competitor, per source type. Daily measurement. Monthly delta memo on ongoing engagements.

We do not execute. No content writing, no website edits, no schema deploys, no profile updates. The labor stays with the customer's team or their agency. That separation is structural.

Pricing

defined term.

  • Monitor — $199/mo.
  • Audit — $750/mo, after a $950 baseline. The baseline is waived on a

[Corrected 2026-09-14. This section published the retired kickoff-plus-monthly card for six weeks after those SKUs were archived on 2026-08-03.]

This is a research engagement, not a SaaS subscription. There is no self-serve dashboard.

Repository layout (current)

neverranked/
├── index.html              honest homepage holder
├── about/, terms/,         current honest pages
│   privacy/, thanks/
├── pitch/asb-hawaii/       current direct-buyer pitch shape
├── pitch/*/                retired pitch pages (holder)
├── blog/, case-studies/,   retired catalogs (holders + noindex)
│   profile/, state-of-aeo/
├── standards/, schemas/,   retired surfaces (holders)
│   agencies/, security/,
│   for-agencies/,
│   principles/, kit/
├── meetings/kits/          current meeting prep, demo bundle
├── dashboard/              app.neverranked.com Worker source
├── llms.txt                rewritten for current state
└── sitemap.xml             homepage only

The historical artifacts (retired pages, audit documents under /audits/, prior explainers like EXPLAINER.md and AGENCY-EXPLAINER.md, the original audit template under /audit-template/) reflect the prior product premise and are preserved for diff context but should not be acted on as current guidance.

Contact

Lance@hi.neverranked.com

Nothing above is checked by us. What we check is on the safety report.

LanceRoylo: common questions

Is LanceRoylo MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the LanceRoylo safety report
How do I install LanceRoylo?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does LanceRoylo need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is LanceRoylo maintained?
The last commit was 38 days ago (2026-09-27). The latest release is v0.1.2.
What can I use instead of LanceRoylo?
Servers from other publishers that do the same job: Roast My Design System MCP server, Kiln MCP server and Roast My Design System MCP server.
How does LanceRoylo compare with other AI and agents MCP servers?
safety score 92/100 (higher than 90% of 4,460 AI and agents servers); tools 3 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to LanceRoylo

Same job from other publishers: the closest match first, then the best rated.

  • Roast My Design System
    Audit your Design System and serve your Agent the rules that keep AI-written UI on-system.
    A
  • Kiln
    Spawn an object into existence: describe it, and your agent designs it, checks it, and 3D prints it.
    B
  • Roast My Design System
    Audit your Design System and serve your Agent the rules that keep AI-written UI on-system.
    A
  • three.ws Provenance
    Append-only, signed, on-chain-verifiable agent action log — record and audit what agents did.
    B
  • Vibe Check
    Metacognitive AI agent oversight: adaptive CPI interrupts for alignment, reflection and safety
    B