AdCockpit is the layer that lets Claude, ChatGPT and every AI analyze, recommend, and act on your paid advertising — across every platform, behind a spend ceiling, a target-market lock, and an audit log.
An allow-list, a spend ceiling, a target-market lock and an append-only audit log wrap every write. Actions are off by default until you turn them on.
Claude, ChatGPT, Cursor, Gemini — one URL. AdCockpit runs underneath the assistant you already use. Protocol- and model-agnostic.
Google Ads, GA4, AppsFlyer today; Meta, X and Yandex next. One neutral schema across all of them — no platform's home turf.
Optmyzr wants you in Optmyzr. Google wants you in Google Ads. We want you nowhere new — you stay in the AI you already talk to, and AdCockpit works underneath it.
And here's the part only a third party can own: the company that sells you ads can't be the one that polices your ad spend. That layer has to be neutral, cross-platform, and on your side. That's the layer we build.
In your AI
Illustrative.
So we built the guardrails first. Every action an AI proposes passes through a control layer before a single dollar can move — and writes stay off until you enable them.
Only a small, named set of actions can ever run.
A hard budget limit no action can cross.
Can't push spend outside the geos you set.
Every proposed and applied change, recorded.
Recommendations are grounded in your real metrics — never a fabricated uplift number. Sample data is clearly labelled until you connect a live account.
It doesn't just advise — it acts, then measures what actually happened.
Your ad accounts land in one place.
It reads the signals — leaking geos, bot farms, wasted spend.
Quantified, prioritized, confidence-tagged. No made-up numbers.
One guarded click — ceiling + market lock + audit log.
Track the real outcome. Proof, not a guess.
AppsFlyer as the measurement spine; each platform's own API for actions. Normalized into one schema so your AI reasons across all of them.
One URL, every MCP-native client. Paste it, sign in with Google, and your AI can pull live recommendations and apply guarded actions by chat. Build once — runs everywhere.
No credentials are entered into AdCockpit — you authorize with Google, and each connection only ever sees its own accounts. Before you connect an ad account, every tool returns clearly-labelled sample data so you can try it first.
A one-click listing in the Claude connectors directory is in review.
It's model-agnostic. Used as a connector, the reasoning is done by whatever AI you're already in — Claude, ChatGPT, Gemini — while AdCockpit supplies the grounded, real-data tools and guardrails underneath. Its built-in deep analysis runs on Anthropic's Claude. Either way, every recommendation is grounded in your actual campaign numbers — the model interprets computed data, it never invents statistics.
No. We don't train or fine-tune any model on your data. Every analysis is generated fresh from your current, real numbers — nothing is accumulated into a training set. Your data is used solely to produce your own diagnostics, and it's never sold.
Yes — that's the whole point. Every write passes a control layer first: an allow-list of actions, a spend ceiling, a target-market lock, and an append-only audit log. Actions are off by default until you enable them, and nothing runs without your approval.
Google Ads, Google Analytics 4 and AppsFlyer today; Meta, X and Yandex are next. Everything is normalized into one neutral schema so your AI can reason across all of them.
Connection tokens are encrypted at rest (AES-256) and never exposed to the browser. Campaign data is read only to render your own diagnostics — not sold or shared. Our use of Google data follows the Google API Services User Data Policy, including its Limited Use requirements.
Add the connector URL — adcockpit.io/api/mcp — in your AI client, then sign in with Google. Before you connect an ad account, every tool returns clearly-labelled sample data so you can try it first.
More in our Privacy Policy and Support.