MCP vs Skills: When to Use Which
MCP gives an assistant access to your systems; a skill teaches it your procedure. When each is the right tool, from a team that ships and maintains both.
AI Search Visibility Platform
The RankX AI blog covers how ChatGPT, Claude, Gemini, Grok, Perplexity and Microsoft Copilot choose which brands to name, and what the measurements actually show.
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MCP gives an assistant access to your systems; a skill teaches it your procedure. When each is the right tool, from a team that ships and maintains both.
Claude Skills explained for marketers: what a SKILL.md folder is, how skills work, the types, how to create your own, and how to install your first one.
MCP architecture in plain language: hosts, clients and servers, the two layers, what tools/list and tools/call do, and the 2026 stateless revision.
What a remote MCP server is, how it differs from local, examples worth connecting, how OAuth 2.1 makes one URL enough, and when local still wins.
The MCP servers worth connecting for SEO and marketing work in 2026, every endpoint verified: visibility, keywords, analytics, crawling and publishing.
What Generative Engine Optimization is, how generative engines retrieve and cite pages, how GEO extends SEO, what measurably works and what failed testing.
How to track AI search visibility: run a fixed prompt panel across six AI assistants, measure share of voice over time, and what an AI visibility tracker records.
What answer engine optimisation means, how answer engines select sources, the answer-first structure with controlled-test evidence, and the AEO mistakes to avoid.
GEO vs SEO vs AEO in one comparison: the key differences, whether GEO replaces SEO, what each earns you, and the order marketers should prioritise them in.
How query fan-out turns one prompt into many synthetic searches, what it means for SEO and topic clusters, and how to cover the sub-query space.
Which AI crawlers exist, their user agents, what they fetch, which of them run JavaScript and which do not, and how to verify your pages are reachable.
What the llms.txt file is, what the server-log evidence says about who reads it, why we publish one anyway, and how to create yours in a minute.
Every article here is in the RSS feed, is readable as clean Markdown by adding .md to its URL, and ships in llms-full.txt, the single file that carries the whole corpus for an AI assistant to read in one request. And if Google is your front door, you can add RankX AI as a preferred source (opens in a new tab), which asks your own results to surface more of what we publish.
The 30-day plan
RankX AI’s 30-Day AI Visibility Plan is free: four evidence-graded weeks from baseline to first citations, with a printable workbook and a 48-prompt starter pack.
The whole plan is on the page. No email needed to read it.