Schema MONKEE

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— Data Infrastructure for the Agentic Web —

Stop Writing Schema for Google. Start Architecting Data for the Agentic Web.

Schema Monkee V3 is the data infrastructure layer for the post-search internet. A 3-pass AI pipeline powered by Gemini 3 Flash Preview builds deeply connected @graph entity networks, turns your WordPress site into a native Model Context Protocol (MCP) provider, and feeds verifiable, machine-readable truth to ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews.

Traditional SEO ranked pages. We establish entities. The models already know the difference.

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See Agency & Franchise Pricing

Native MCP · Zero PHP bloat · Delivered by webhook · Automatically supersedes Yoast & RankMath

The Paradigm Shift

Three generations of schema. Only one was built for the agents actually reading it.

For a decade, “SEO schema” meant bolting isolated JSON blocks onto a page and hoping Google’s crawler noticed. That model was built for keyword ranking — not for a web where Claude, ChatGPT, Perplexity, and Gemini negotiate facts in real time. Here’s what changed.

Generation 1 · Dead

Legacy Schema Plugins

Yoast · RankMath · Early JSON-LD tools

Flat. Isolated. Ranking-era.

Generates one-off schema blocks per page — an Organization here, an Article there — with no shared identity layer. @ids are missing or duplicated. Every page is an island. Built to tick a Rich Result box — not to answer a machine’s question.

  • Per-page JSON snippets, not a graph
  • No @id strategy, no cross-entity links
  • Authored for SERP snippets
  • Invisible to MCP-aware agents
  • Runs as heavy PHP on every page load

Generation 2 · Shallow

First-Gen “AI-SEO” Tools

The copycats · Single-pass generators

Shallow wrappers. New labels. Same flat data.

A wave of tools slapped “AI” onto the same old output — adding an llms.txt file or an FAQ block and calling it agent-ready. Underneath, the schema is still flat, entities still don’t link, and the “Golden Source” business data is whatever the model hallucinated on the first pass. No enforcement. No authority layer. No proof.

  • Single-pass generation — no enforcement
  • Hallucinated NAP data ships to production
  • No Wikidata grounding, no sameAs chain
  • No measurement of AI citation share
  • “MCP support” is a static file, not a live provider

Generation 3 · The Future

Schema Monkee V3

Data architecture for the Agentic Web

Deeply connected @graph. Enforced truth. Native MCP.

One entity network — not a pile of blocks. Every Organization, Person, Service, and Place gets a unique @id and is woven into a single machine-readable graph. A 3-pass Gemini pipeline generates, enforces your Golden Source, and perfects the architecture to Schema.org-authority standards. Your site becomes a live MCP provider — not a file, a service.

  • Nested @graph with full entity linking
  • Pass 2 overrides AI hallucinations with your verified NAP
  • Automated Wikidata claims cite your site as source
  • AI Visibility Tracker — ChatGPT, Claude, Gemini, Perplexity, AI Overviews
  • Live /llms.txt and /.well-known/mcp.json
  • Cloud-generated JSON-LD pushed by webhook — zero runtime PHP

Flat schema told Google what you are. Connected entity graphs tell every agent on the web who you are, what you do, and why you’re the source of truth. That’s the upgrade.

See the 3-Pass Pipeline in Action →

The Platform

Four systems. One source of truth.

Every Schema Monkee site runs on the same four-layer stack — a generation pipeline that never ships hallucinations, a live MCP provider the agents can actually query, a visibility tracker that proves the work, and a Wikidata bridge the models already believe. Here’s what each one does.

01

Pipeline

Three passes. Zero hallucinations in production.

Every site runs through three specialized AI passes on Gemini 3 Flash Preview — because single-pass generators ship whatever the model guesses on the first try. Our pipeline separates creation, verification, and expert optimization into distinct stages, so your published knowledge graph reflects your real business, not the model’s hallucination of it.

  • Pass 1 — Generate: ingests up to 100,000 characters and builds the initial @graph from scratch, applying mandatory Schema.org rules.
  • Pass 2 — Enforce: locks in your Golden Source data — exact name, parsed address, verified phone — overriding any AI invention.
  • Pass 3 — Perfect: rebuilds entity architecture, relationship chains, E-E-A-T signals, and sameAs authority links at Schema.org-authority level.

02

MCP

Your WordPress site becomes a live AI data source.

Static llms.txt files are a bookmark. Schema Monkee turns your WordPress site into a native Model Context Protocol provider — the same interface Claude Desktop, Cursor, and every MCP-aware agent already speak. When an AI needs to know something about your business, it queries you directly, in real time, with full entity resolution.

  • Live endpoints, auto-maintained: /llms.txt and /.well-known/mcp.json generated from your stored schema — no manual authoring, no drift.
  • Queryable by any MCP client: Claude Desktop, Cursor, and the growing fleet of agent platforms can interrogate your graph structurally, not by scraping HTML.
  • Always current: every Pass 3 update fires the same webhook — the agents always see the canonical version.

03

Visibility

Measure your presence where the answers actually live.

Traditional SEO dashboards report rankings on a page almost nobody visits anymore. Schema Monkee’s AI Visibility Tracker reports whether ChatGPT, Claude, Gemini, Perplexity, or Google AI Overviews actually mentioned you in the answer your customer just read. Dual-detection combines browser automation with computer vision, so we capture what the AI actually shows — not just what it claims to return.

  • Dual-detection engine: Playwright runs real queries in real browsers; Gemini Vision reads the rendered answer card like a human — catching visual citations and logo mentions text scrapers miss.
  • Five surfaces tracked continuously: Google AI Overviews, ChatGPT, Claude, Perplexity, and Gemini — the channels where customers ask product questions today.
  • Citation-grade metrics: bounding-box position, visual real estate share, competitor co-mentions, and sentiment on every appearance.

04

Authority

Cement your place in the knowledge graph every LLM was trained on.

Every major language model was trained on Wikidata. Claims that cite your website as the reference source become first-class facts inside the models now answering your customers’ questions. Schema Monkee finds your entity, matches it, and keeps those claims current — automatically, and with your domain as the cited authority.

  • Automatic entity matching: we locate your organization, key people, and locations on Wikidata and wire them into your @graph via sameAs.
  • Cited claims, not raw edits: property updates are submitted with your verified website as the referenced source — the signal Wikidata (and every LLM) weights most heavily.
  • An undeniable foundation of trust: once Wikidata cites your site as source, downstream models treat your data as canonical.

Four layers. One promise: your business data arrives at every AI surface verified, connected, and cited back to you.

Explore the Full Architecture →

Built for Operators

The easiest “AI Readiness” upsell your agency has ever shipped.

Every agency is being asked the same question this quarter: “Are we ready for AI search?” Schema Monkee lets you answer “yes” on Monday — with white-labeled proof by Friday. For franchise operators, it’s the only platform that treats a 40-location brand as one entity network, not forty disconnected sites.

For Marketing Agencies

Stop selling schema. Start selling AI Readiness — at agency margins.

“SEO audits” are a commodity. AI Readiness reports are a $2K/month retainer. Schema Monkee ships the full product on day one — vector-perfect client PDFs, measurable scores your clients can forward to their CMO, and native GoHighLevel integration so the whole workflow lives inside the CRM you already run. You become the agency with proof — while competitors are still explaining what MCP means.

  • White-labeled vector PDF reports — rendered at print quality with your logo, palette, and domain. Three numbers clients can grade you on: Schema Health Score, Rich Result Eligibility, and AI Visibility Score.
  • Native GoHighLevel integration via the ATM proxy — Schema Monkee ships as an Agentic Tools Mobile (ATM) proxy inside GoHighLevel. Audits, reports, and re-generation fire from the same workspace your account managers already live in.
  • The only “AI Readiness” SKU with receipts — every deck claim backed by a live number: citation share on Perplexity, bounding-box position on AI Overviews, sentiment on ChatGPT. Retainers renew themselves.
See a Sample White-Label Report →

For Franchise Operations

One brand. Forty domains. One connected entity network.

Every legacy schema plugin treats each location’s WordPress site as an island. Schema Monkee treats them as siblings of the same parent organization — automatically mapping parentOrganization, subOrganization, and sibling @id references across every domain in your franchise_network database. When an agent asks about any location, it understands the entire brand.

  • Automatic subOrganization injection across every franchisee domain — each location’s @graph carries the exact parent @id. Google and every LLM see a coherent brand, not 40 LocalBusinesses competing for the same queries.
  • Cross-domain sibling awareness (Pass 2) — the enforcement pass knows Dallas, Denver, and Detroit are siblings of the same franchisor, with consistent parent data and distinct Golden Source NAP per location.
  • The franchise_network database tracks the graph, not just the sites — new locations inherit the correct parent and sibling structure on day one. An acquisition becomes one record change, not a 40-site schema migration.
Map Your Network →

Agencies prove the ROI. Franchises get one source of truth across every location. Both ship from the same platform — because the Agentic Web doesn’t care whether you’re one business or four hundred. It only reads the graph.

Talk to Agency Sales →
Book a Franchise Architecture Review

For Developers

A schema plugin built for servers that already have enough to do.

Let’s address the objection head-on. Most “AI SEO” plugins ship a vendored Python parser, a cron job firing Gemini calls from your PHP-FPM pool, and API keys living in wp-config.php. Schema Monkee does none of that. The 3-pass pipeline runs entirely in our cloud. Your server receives exactly one thing: a signed webhook carrying finished JSON-LD. WordPress stays fast, predictable, and auditable — the way you shipped it.

[Schema Monkee Cloud]
   Pass 1 · Generate
   Pass 2 · Enforce   (Golden Source NAP, sibling awareness)
   Pass 3 · Perfect   (entity architecture, sameAs, E-E-A-T)
           │
           │  HMAC-signed POST
           ▼
[Your WordPress]
   /wp-json/sm/v1/schema  →  update_option()  →  wp_head JSON-LD

One inbound write. No outbound AI traffic from your server. Ever.

Three promises your ops team will verify.

  • Cloud-to-webhook delivery — zero runtime PHP in the hot path. Gemini, Wikidata, Playwright, and Vision all run on our infrastructure. The plugin wakes up to validate an HMAC signature, write the perfected @graph to one option, and go back to sleep. No PHP workers blocked. No AI keys on your box. No surprise egress bills.
  • Sub-10KB footprint. No cron, no scanners, no AJAX loops. The plugin adds one REST endpoint, one wp_head filter, and nothing else. TTFB doesn’t change. Query Monitor stays clean. Deactivate it and the site is byte-identical to before — no orphaned tables, no phantom transients.
  • Intelligent supersession of Yoast and RankMath. When Schema Monkee’s schema is present, we automatically suppress the legacy plugins’ JSON-LD output — no remove_filter gymnastics, no duplicate Organization blocks fighting for the root @id. Yoast and RankMath keep their meta titles, sitemaps, and XML. We own the graph. One source of truth. Zero conflicts.

Signed HMAC · Write-only scope · No outbound internet from the plugin · Works on WP Engine, Kinsta, Pantheon, Cloudways, and any bare-metal LEMP · Page-cache- and object-cache-safe · CSP-friendly inline output

Modern WordPress should feel like a delivery surface, not a runtime for somebody else’s AI stack. That’s exactly what we built.

Read the Webhook Contract →
View Plugin Source on GitHub →