— Practice / Agent-ready
Build for the agents doing the reading.
A growing share of the traffic that matters is an AI agent or answer engine reading on someone’s behalf. Most sites are close to invisible to them. We make yours legible, and give agents a way to act on it as well.
— The shift
Search is splitting in two.
People increasingly ask ChatGPT, Perplexity, Claude, and Google’s AI Overviews instead of working through a page of links. Those systems answer from what they can read cleanly and attribute confidently. A site built from unlabelled markup is not broken. It is simply absent from the answer. Agent-ready sites stay quotable as that shift continues.
— What we do
The work, plainly.
llms.txt
A curated, machine-readable map of your site (what you do, your key pages, your terms) that answer engines read directly instead of inferring it from HTML.
Structured data
schema.org JSON-LD so engines resolve you as one consistent entity across the web, instead of guessing afresh on every page.
AI-crawler policy
robots.txt and Content-Signals that state, in machine-readable terms, how AI systems may use your content. Silence is a decision made for you.
Markdown for agents
Serve a markdown version of a page on request, so a model spends its context on your content rather than your markup. It is cheaper to ingest and likelier to be cited.
MCP server
A Model Context Protocol endpoint so agents can call your site as a tool: search it, price a job, start a conversation. Few sites have one yet.
Generative-engine optimization
The on-page structure answer engines lift: direct answers up top, comparison tables, visible freshness, and the entity signals that decide whether you are the source they cite.
— The proof
We shipped it on our own site first.
Most of this runs on our own site: an llms.txt, structured data on every page, an AI-crawler policy, blog posts that return markdown on request, and a public MCP server you can install in Claude or Cursor today. Run the audit on us. You will see where we score well and which gaps we are still closing.
Our MCP server lives at https://setkernel.com/mcp. The server card is at https://setkernel.com/.well-known/mcp/server-card.json.
Run the free AI-readiness audit— Questions
Common questions.
Is this just SEO with a new name?
It overlaps, but no. Classic SEO tunes how you rank in a list of links. Agent-readiness covers the surfaces that decide whether an AI system can read, trust, and cite you at all: llms.txt, structured data for entity resolution, AI-crawler policy, markdown negotiation, and an MCP server. A site can rank well and still be invisible to an answer engine.
Do I actually need an MCP server?
Not always, and not first. Most sites get the biggest gain from llms.txt, clean structured data, and an explicit crawler policy. An MCP server earns its keep when you want agents to do something on your site, such as look something up, start an enquiry, or run a calculation. We will tell you where that line falls for you.
How do you measure agent-readiness?
Start with the free AI-readiness audit on this site. It scores llms.txt, structured data, AI-crawler policy, the basics, sitemap, markdown negotiation, and MCP, and shows you exactly which are present. If you want us to close the gaps, that is a written brief and a scoped quote.
Will this hurt my normal search rankings?
No. Everything we add (structured data, a sitemap, clean metadata, a curated content map) is neutral or positive for classic search. Agent-readiness and traditional SEO pull in the same direction. They measure different halves of the same job.
— Engage
Want to be in the answer, not just the index?
Run the free audit, or write us two paragraphs: what your site is, who you want reading it, and what done looks like. We reply in writing within one business day.