[ 01 ] / hero

Make your business legible to AI agents.

Consulting and implementations for MCP, UCP, and structured data — so AI agents can find, understand, and recommend your business.

Get a readiness check See what we do

MCP · UCP · Schema.org · JSON-LD · llms.txt · structured data · agentic search · readiness audits

organization.jsonld

valid

01{
02  "@context": "https://schema.org",
03  "@type": "Organization",
04  "name": "supai.bot",
05  "url": "https://supai.bot",
06  "slogan": "Make your business legible to AI agents.",
07  "knowsAbout": [
08    "Model Context Protocol",
09    "Schema.org", // + 4 more
10  ]
11}

[ 02 ] / the shift

AI agents are becoming the recommendation layer.

Search is unbundling. Your customers ask Claude, ChatGPT, and Perplexity what to use, what to buy, and who to trust — then act on the answer. Sites that aren’t legible to these agents lose mindshare invisibly. No warning. No referrer ping. No chance to respond.

The fix isn’t more content. It’s structure agents can parse, actions agents can take, and protocols agents already speak.

No referrer, no signal

Agentic traffic often arrives without analytics fingerprints. If you can't measure it, you can't optimize for it. Most teams don't even know it's happening.

ii.

Citations replace clicks

Agents synthesize answers. Being cited matters more than ranking #3. The new SEO is structured-data SEO.

iii.

Structured beats clever

Agents read JSON-LD, MCP manifests, and llms.txt before your hero copy. Brilliant headlines lose to boring schema.

[ 03 ] / what we do

Four ways we make your business machine-readable.

[ 01 ] / MCP Implementation

↗

Model Context Protocol servers that do work.

We design, build, and host MCP servers that let AI agents take real action on behalf of your business — book, quote, query, transact. Not chatbots. Capabilities.

▸Server architecture, tool surface, auth model
▸Production hosting, observability, rate-limiting
▸Compatibility tested against Claude, ChatGPT, and major MCP clients

[ 02 ] / UCP Implementation

↗

Universal context, vendor-neutral.

Universal Context Protocol surfaces let any agent — not just one vendor — route, summarize, and recommend you correctly. UCP is emerging; we'll tell you where it's earning trust and where it's hype.

▸Vendor-neutral context surfaces
▸Federation strategy across agent ecosystems
▸A migration path that doesn't lock you in

[ 03 ] / Schema.org & Structured Data

↗

The unsexy fundamentals, done well.

JSON-LD, OpenGraph, sitemaps, llms.txt, robots tuning. Most of what gets sold as “AI SEO” is just doing this part properly — and most sites still don't.

▸Entity, product, and content schema across the surface
▸llms.txt, sitemap, and crawler access policy
▸Validation in CI so it doesn't regress

[ 04 ] / AI Readiness Check

↗

A point-in-time audit. Real fixes, ranked.

We crawl, parse, and probe your site the way an agent would, then ship a prioritized punch list. No fluff. No 80-page deck. Just what to fix and the order to fix it in.

▸50+ checks across schema, MCP, content, and crawl access
▸Severity-ranked findings with effort estimates
▸An implementation roadmap your team can execute

[ 04 ] / how it works

Three steps. Done in weeks, not quarters.

01
Audit
We map your surface area the way an agent does — schema coverage, MCP availability, crawl access, content legibility, citation likelihood. You get the same view a model gets.
02
Implement
We ship the fixes. JSON-LD across the entity graph, MCP servers in production, llms.txt and sitemap done right, content restructured for parse-ability — whatever the audit named.
03
Verify
We re-probe with multiple agents. You get a measurable before/after, plus instrumentation to track agent traffic going forward. Then you own it.

[ 05 ] / what we believe

i.
Bots are users now.
Treat agents as a first-class audience — not a footnote in robots.txt. Your CFO will care once your competitor gets cited and you don't.
ii.
Structured beats clever.
A boring JSON-LD block out-performs a brilliant headline if the agent never reads the headline. Optimize the page that the model actually sees.
iii.
Verify, don't assume.
Every claim about being “AI-friendly” should be measurable against an actual model. We test with the real ones. So should you.

[ 06 ] / get in touch

Tell us what’sup.

Audit, implementation, or a real conversation about whether you need either. We respond within one business day.

email: hello@supai.bot
response: ≤ 1 business day
based: remote · worldwide