AI Search Visibility Platform
How brands get named in AI answers.
The RankX AI blog covers how ChatGPT, Claude, Gemini, Grok and Perplexity choose which brands to name, and what the measurements actually show.
Every article answers one question about how retrieval and citation work across the 5 tracked assistants: what moves a brand’s share of answers, what the evidence says once somebody runs the test instead of asserting the result, and how to run the whole job from inside Claude.
Browse by topic
- AI Agents and MCP7 articlesStart with AI Agent SEO: Run an Audit From Inside Claude
- AI Visibility Measurement2 articlesStart with How to Measure and Track AI Search Visibility
- GEO Fundamentals6 articlesStart with Generative Engine Optimization: A Complete Guide
Latest from RankX AI
AI Agent SEO: Run an Audit From Inside Claude
An AI agent for SEO is an assistant that works your SEO data with tools rather than advice. Connect RankX AI to Claude over MCP and the agent audits your AI visibility on request: where your brand appears in AI answers and Google AI Overviews, which competitors take the citations you miss, and what to fix first, read-only by default.
How to Add the RankX AI MCP Server to Claude
Claude connects to RankX AI over MCP in under a minute. In Claude Desktop or Claude Web, add a custom connector pointing at the RankX AI endpoint and sign in with OAuth. In Claude Code, run one claude mcp add command with either OAuth or a personal access token. An account owner approves the connection once.
MCP vs Skills: When to Use Which
MCP and skills solve different problems. An MCP server gives an AI assistant access: tools it can call against a live system, with authentication and permissions. A skill gives it procedure: written instructions for doing a job well, usually with those tools. Missing access needs MCP; a sloppy process needs a skill.
What Are Claude Skills? A Marketer's Guide
Claude Skills are folders of instructions that teach Claude how to do a specific job well. Each skill is a SKILL.md file with a name, a description and step-by-step guidance, optionally bundled with scripts and reference files. Claude loads a skill only when the task matches its description, so expertise costs almost nothing until it is needed.
MCP Architecture, Explained Without the Jargon
MCP, the Model Context Protocol, is an open standard that lets an AI assistant call tools on external services through one common interface. The architecture is client-server: a client asks a server what tools it offers, the model picks one, the client calls it, and the result comes back as data. Everything travels as JSON-RPC 2.0 messages.
Remote MCP Servers: Why They Beat Local
A remote MCP server runs as a hosted service you connect to over HTTPS, instead of a program installed on your machine. You paste one URL into your AI client, sign in with OAuth, and approve once. Nothing installs, credentials stay server-side, every user gets the current version, and web-based clients can connect at all.
Best MCP Servers for SEO and Marketing in 2026
The best MCP servers for SEO in 2026 are official vendor servers, most now remote: RankX AI for AI search visibility, Ahrefs, Semrush, DataForSEO and SE Ranking for keyword and backlink data, Google's own server for Analytics, Screaming Frog for crawling, and Automattic's WordPress server for publishing. Every entry here was verified on 20 August 2026.
Generative Engine Optimization: A Complete Guide
Generative Engine Optimization (GEO) is the practice of making a brand and its pages retrievable, quotable and recommendable by generative engines such as ChatGPT, Google AI Overviews, Perplexity, Claude, Gemini and Grok. It extends SEO: the same crawlable, well-structured content, written and organised so generative AI systems can extract it and name you.
How to Measure and Track AI Search Visibility
AI search visibility is how often your brand appears in AI answers. Measuring it means tracking the share of answers naming your brand across a prompt panel, on every AI platform your buyers use, repeatedly. Single checks are noise because answers change between runs; the defensible stack is share of voice plus crawler logs and Search Console data.
What Is Answer Engine Optimization (AEO)?
Answer Engine Optimization (AEO) is the practice of structuring content so answer engines like ChatGPT, Google AI Overviews and featured snippets can extract it and present it as the answer. In practice that means answer-first pages: a direct answer at the top, question-shaped headings, and sections that survive being quoted alone.
GEO vs SEO vs AEO: What's the Difference?
SEO earns retrieval: crawlable pages, resolvable entities and rankings in a search index. AEO earns extraction: answer-first structure an engine can quote. GEO is the umbrella covering both plus off-page reputation, aimed at AI answers. Prioritise SEO first because it gates the other two, then apply AEO structure to every page.
Query Fan-Out: One Prompt, Twenty Searches
Query fan-out is how AI search engines expand one prompt into many synthetic sub-queries and search for each simultaneously. Google confirmed the technique for AI Overviews and AI Mode in 2025. Pages win citations by matching sub-questions rather than the visible prompt, which is why covering adjacent questions beats chasing the head term.
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, which asks your own results to surface more of what we publish.