Integration4 min read2026-07-31

AI visibility in Bubble

Bubble builders reach for AI-visibility data for a different reason than most: not to watch their own brand, but to ship the feature. A marketing dashboard, an SEO tool, a client portal — "what does ChatGPT say about you" is a screen your Bubble app can own, with AgentGEO as the invisible data layer underneath. The wiring is the API Connector plugin against one REST contract — no AgentGEO plugin in Bubble's marketplace, and this page won't pretend otherwise. The design that works: keep the slow scraping on AgentGEO's side (schedules), let Bubble make fast reads, and store the records in your own database so your charts render from your data.

Read this page with an AI

Records arrive as structured JSON — per-engine answerText, sources[] with title, URL and position, run metadata — which the API Connector maps into Bubble types your repeating groups and charts consume directly.

Connect AgentGEO to Bubble

In the API Connector, add an API named AgentGEO with a shared header Authorization: Bearer ag_live_... (kept private, server-side), then two calls:

  1. List runsGET https://api.agentgeo.org/v1/runs?limit=10, initialized as Data. Returns run summaries: id, query, status, recordsDelivered, timestamps.
  2. Get runGET https://api.agentgeo.org/v1/runs/[id], with id as a URL parameter. Returns the full envelope including per-surface answers and citations.

Then a backend workflow on a schedule: call List runs, and for each completed run not yet in your database, call Get run and create one Answer thing per delivered record — engine, answer text, cited URLs, run ID. Your pages read from your own Answer type, never live from the API, so screens stay instant and your history survives any vendor decision.

Avoid wiring POST /v1/fetches into a page-load or button action: the API can hold that request up to 180 seconds while live engines answer, which is far past what a good Bubble UX (or patient user) tolerates. Create schedules server-side — in the AgentGEO console or via POST /v1/schedules — and let your backend workflow file results as they land.

What to build once it's connected

  • A visibility tab in your SaaS. Repeating group over Answers grouped by engine, a "cited / not cited" state computed against the customer's domain — the full product case is the embed use case.
  • Client portal for an agency. One Bubble app, one page per client, charts over their filed records — the delivery layer for white-label GEO reports.
  • Citation explorer. A searchable repeating group over every cited source your queries have ever returned — which domains do the engines trust in your category, and is yours among them?
  • Change alerts. A backend workflow that compares the newest run's cited set to the previous one and emails the workspace owner when your domain appears or drops.

More integrations

If Bubble is your frontend but not your automation home, pair it with n8n or Pipedream doing the fetching into the same database. The raw contract lives in the cURL guide; all platforms are at all integrations.

Scope the feature against real records: Get a free AI-visibility audit → · Docs →

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FAQ

Direct answers to the questions this page raises.

No — the built-in API Connector covers everything: a private Bearer header, two GET calls for reading runs, and optionally POST /v1/schedules for managing schedules from your app. Fewer moving parts than a plugin, and nothing to fall out of date.

Design it as "request a check", not "wait for a check": the button creates or nudges a schedule, and your backend workflow files the results into the database minutes later — a notification beats a three-minute spinner. Live fetches can legitimately hold up to 180 seconds, which no page action should sit through.

Only if you tell them. Calls are server-to-server with the key in a private header, records land in your database, and your UI renders your charts. The API has no end-user surface and no branding in the payload.

One credit per delivered record, zero for failed fetches, and all the polling reads are free. Per customer, cost is queries × engines × refresh cadence — a spreadsheet you can price your own tiers from, with a spend cap so it can't run away. Build against ag_test_ demo keys first; live keys are minted in the console and come with a plan.

Keep reading

Where this page leads next.

Run these checks on your own brand

Two ways in. Send a URL and a person runs the fetches for you, free — or connect your agent over MCP, on a plan, and run them yourself. Either way you get the raw answers and their citations, never a score.