— The Technology —

The stack that replaces “SEO” for the post-search internet.

Schema Monkee V3 isn’t a plugin — it’s a four-system platform. A 3-pass AI pipeline generates and verifies your entity graph. A native MCP server turns your WordPress site into a live AI data source. An AI Visibility Tracker measures your presence in the answers LLMs give. A Wikidata bridge cements your place in the knowledge graph every model was trained on. They’re designed to work together — and each one is documented below.

System Architecture

How the four systems work together.

Your content is the input. The entity @graph is the source of truth at the center. Everything else exists to produce it, serve it, or verify it.

The Four Pillars

Pick the system you want to understand first.

01

Generation

The 3-Pass AI Pipeline

Gemini 3 Flash Preview runs your content through three specialized passes — Generate, Enforce, Perfect. Single-pass generators publish hallucinations. Ours publishes your verified entity graph.

02

Integration

Native MCP Server

Your WordPress site becomes a live Model Context Protocol provider. Claude Desktop, Cursor, and every MCP-aware agent can query your knowledge graph in real time — not by scraping your HTML.

03

Measurement

AI Visibility Tracker

Dual-detection — Playwright renders real queries, Gemini Vision reads the answers. Continuously tracks your presence across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews.

04

Authority

Knowledge Graph Bridge

Every LLM was trained on Wikidata. We match your entity, submit claims with your site as the referenced source, and cement your place in the global knowledge graph. Facts become canonical.

Why Four Systems, Not One

The monolithic “AI SEO tool” is a category error.

Generating schema, serving it to agents, verifying it against external authorities, and measuring whether those agents actually cite you are four different problems. Bundling them into one plugin forces compromises in every direction — generation gets cheap, serving gets flat, verification gets skipped, measurement doesn’t exist.

Schema Monkee V3 treats them as what they are: four production systems that share one data model. The pipeline is optimized for correctness. MCP is optimized for agent latency. Visibility is optimized for citation-grade detection. Wikidata sync is optimized for authority signal. Each one is replaceable. Each one is separately auditable. That’s the stack.

See the whole stack on your site.

A free audit runs your homepage through Pass 1, tells you what the model invented, shows you what your current Wikidata footprint looks like, and reports whether any of the five major AI surfaces currently cite you. Five minutes. No install.