Google Ads to ChatGPT in 2026: 4 free ways to connect

boltTL;DR

To connect Google Ads to ChatGPT:

Sign up free at portermetrics.com and connect your Google Ads account with your Google account.
In ChatGPT, click + → Connectors → Manage connectors → Add custom connector, name it Porter, paste https://mcp.portermetrics.com/mcp, then click Add and authenticate with Google.

That’s it, you’re connected. Porter’s free plan covers up to 3 Google Ads accounts with no usage limits on ChatGPT’s free plan. No credit card required.

What makes Porter different:

Read + write, safely. Porter’s MCP lets you create, update, and delete Campaigns, Ad Groups, Responsive Search Ads, Keywords, and extensions (sitelink, callout, call, snippet) from inside ChatGPT, through deterministic code components. Campaigns are created in PAUSED by default so you can review before going live. Nothing hallucinates, and built-in rate limiting keeps your account safe from bans.
1,042+ Google Ads metrics and dimensions, and the only MCP that includes attribution coverage in the same connection.
Universal Google Ads MCP. Hosted white-label dashboards and client portals, competitor tracking with Auction Insights competitive analysis, and automated campaign management with deterministic guardrails. Your whole Google Ads operation runs from one chat.

Animated demo of asking ChatGPT for marketing data via Porter Metrics — Example Google Ads client dashboard generated in ChatGPT using live data from Porter MCP.

Prerequisites

A Porter Metrics account with your Google Ads account connected (free tier is enough to try it end-to-end)
A ChatGPT account — the free plan works for ChatGPT Web; a Pro subscription is needed for Codex and Desktop MCP features
Admin or standard access to the Google Ads accounts you want to connect

Connect Google Ads to ChatGPT with MCP

For this tutorial we’re going with the MCP method. Here’s a quick explainer of what MCP is and why it’s the best path for Google Ads.

MCP (Model Context Protocol) is the open standard that lets AI tools like Claude, ChatGPT, Codex and others access and use external APIs — the things that make tools like Google Ads work under the hood. Instead of building a custom integration for every AI tool you use, you install one MCP and every compatible AI gets access to the same data.

Four reasons MCP wins for Google Ads:

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Copy-paste setup

No tokens, no scripts, no developer help — literally paste one URL into ChatGPT and you’re done.

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Works with every AI tool

Claude, Codex, ChatGPT, Cursor, Antigravity, Lovable, Vercel v0, Zapier. One MCP URL, every tool that speaks the protocol.

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20+ sources in one connection

Porter’s MCP ships Google Ads plus Meta Ads, GA4, Shopify, HubSpot, Klaviyo, Google Sheets and 20+ more. Query and blend them all in a single conversation.

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Perfect granularity

Spreadsheets lock you into the columns you exported. MCP hits Google’s API directly — so you can filter by campaign, break down by ad group or keyword, and add new dimensions on the fly without rebuilding tables.

The full setup takes under 5 minutes and breaks into three moves: connect Google Ads to Porter, point ChatGPT at the Porter MCP, and ask your first question.

Two ways to connect Porter to ChatGPT. This tutorial uses the Porter MCP (recommended): you paste one URL, and every new tool or data source is available the moment the Porter team ships it. Prefer one click? Porter Metrics is also an approved app in the ChatGPT marketplace — same account, same live data, but app updates only land after ChatGPT reviews them, so the newest capabilities always arrive on the MCP first. Jump to the marketplace steps ↓

1. Connect your Google Ads data to Porter

Porter sits between Google’s Google Ads API and ChatGPT. It handles OAuth, rate limiting, pagination and all the plumbing so ChatGPT only ever sees clean, structured data.

Sign up for Porter. Create a free account at portermetrics.com. The free tier is enough to run this full workflow end-to-end.

Connect your Google account. In Porter, click Create → pick ChatGPT as the destination → select Google Ads as the source → sign in with Google to grant access to your accounts.

Sign in with Porter Metrics prompt to authorize ChatGPT

Select your accounts. Choose the Google Ads accounts you want ChatGPT to query. When you select multiple accounts under a single connection, Porter automatically blends their data together so you can query them as one.

Porter Metrics is now connected to ChatGPT confirmation

Optional: enable automatic BigQuery storage if you’re connecting multiple accounts with large data volumes. This keeps ChatGPT’s responses fast even at scale.

2. Connect the MCP to ChatGPT

Porter’s MCP URL is what you paste into ChatGPT. Once added, ChatGPT can query Google Ads data on demand in any conversation.

Go to chatgpt.com and click the + icon in the chat input to open the tools menu.

Open the plus menu in the ChatGPT composer to add an app

In the menu that opens, hover over Connectors and click Manage connectors.

ChatGPT More menu showing Add sources to connect Porter Metrics

In the Connectors panel, click the + button at the top of the list to start adding a new connector.

Searching for the Porter Metrics app in ChatGPT

Pick Add custom connector from the dropdown that appears.

Porter Metrics app page in ChatGPT with the Connect button

A dialog opens with the name and URL fields. Type Porter in the first field to name the connector.

In the second field, paste https://mcp.portermetrics.com/mcp. Leave the advanced settings alone.

Click Add at the bottom right of the dialog. ChatGPT opens a sign-in window — use the same Google account linked to your Porter workspace and approve access.

Once the authorization finishes, you’ll see Porter’s tools appear in the connectors panel. You’re ready to start asking questions (and, for connectors that support it, running actions).

Porter Metrics attached in a new ChatGPT chat

For a fuller walkthrough with screenshots at every step, see the Porter MCP tutorial.

3. Start building questions and dashboards

With Porter connected, open a new ChatGPT chat and ask anything about your Google Ads in plain English. ChatGPT calls Porter behind the scenes, pulls live data from Google, and answers with tables, charts, or summaries.

Try one of these to verify the setup is working:

chat_bubble“Show me my top 5 campaigns by Cost last 7 days, ranked by ROAS.”

chat_bubble“Which keywords have a Quality Score below 5 and are costing me the most in inflated CPCs?”

chat_bubble“Compare my Search Impression Share this month vs last month for every active campaign.”

For a full catalogue of copy-paste prompts organized by use case (campaign management, budgets, creatives, performance, agency, e-commerce, cross-channel), jump to the prompts section below.

Alternative ways to connect Google Ads to ChatGPT

Porter MCP is the path we just walked through and the one we recommend for most marketers. It is not the only way to get Google Ads data in front of ChatGPT, though. The most common alternatives are Google Ads’s direct API, a live Google Sheets bridge or CSV upload, and BigQuery for scale. Each has trade-offs, so pick the one that fits how your team already works.

🔌 Google Ads’s direct API — Talk to Google’s Google Ads API yourself. Maximum control, but you handle auth, rate limits and pagination — and you only get one source. (Google doesn’t ship an official MCP yet.)
📊 Google Sheets — Live Sheet or one-off CSV upload. Auditable, familiar, faster for big exports — but aggregation happens in the Sheet, not the API.
🗄️ Google BigQuery — For large accounts or agencies running multi-account analysis. BigQuery aggregates; ChatGPT only queries pre-built summaries.

Via the Porter Metrics app in the ChatGPT marketplace

If you’d rather not paste a connector URL, install Porter straight from ChatGPT’s app gallery — it’s the same Porter connection behind the scenes, published as an approved ChatGPT app:

Open the Porter Metrics app page in ChatGPT (or search “Porter Metrics” in the apps gallery).
Click Connect and sign in with the same account you use in Porter.
Authorize it and ask your first Google Ads question — same live data as the MCP.

The trade-off to know: the marketplace app only updates after each ChatGPT review cycle, while the MCP updates the moment Porter ships. If you want every new tool and data source immediately, use the MCP; if you want the one-click install and don’t mind waiting for new features, the marketplace app is the shortest path — including write actions through your connected Porter account.

Via Google Ads’s direct API

If you’re building a product around Google Ads — or you’re a developer who’d rather own every layer of the integration — the most direct path is talking to Google’s Google Ads API yourself, or — where it exists — Google Ads’s own official MCP. Google doesn’t ship an official Google Ads MCP as of June 2026. Whichever route you pick, you still follow Google’s rate limits & quotas. Either way you skip Porter and call Google from your own code, from Codex, or from Google Ads’s own connector.

The trade-off to know Going direct gives you maximum control and the freshest possible data — every endpoint, every parameter, no abstraction layer in between. But you’re now responsible for OAuth flows, refresh tokens, rate limits, pagination, schema changes, and error retries. And critically, you only get one source. The moment you also want Meta Ads, GA4 or Shopify in the same conversation, you’re back to building (or stitching together) more integrations.

When this makes sense: engineering teams that need a single source with full control, products that ship Google Ads data as a feature (where you own the integration anyway), or one-off scripts where you don’t mind writing the auth and pagination code yourself. For marketers who want to ask questions in plain English and blend Google Ads with the rest of their stack in a single conversation, the Porter MCP path is dramatically less work.

Via Google Sheets (live Sheet or manual CSV)

If your team already lives in Google Sheets — or you want a paper trail before ChatGPT touches anything — feed Google Ads into a Sheet, then let ChatGPT read the Sheet. You can automate the Google Ads → Sheets pipeline with Porter so it refreshes daily, or do one-off CSV exports from Google Ads’s native UI for static analysis.

The trade-off to know With the MCP path, ChatGPT calls Google’s API directly and Google does the filtering and aggregation on its side — clean and deterministic. With the Sheets path, ChatGPT aggregates inside the Sheet itself, which can introduce hallucinations on totals, averages, and joins when you have thousands of rows. The upside is speed: for very large date ranges or historical analysis, a pre-built Sheet is dramatically faster than live API calls.

When this makes sense: finance teams that want to review numbers before ChatGPT acts on them, agencies already delivering client reports in Sheets, historical analysis across years of data, or any case where you care more about speed than real-time freshness.

Via Google BigQuery (for scale)

This is the path most people overlook — and it’s the one that saves you when your Google Ads account gets serious. A single large advertiser or an agency managing 10+ accounts will hit API rate limits and latency problems querying ChatGPT directly. ChatGPT will literally tell you it’s taking too long or timing out on big pulls.

BigQuery fixes that. You load Google Ads data into BigQuery tables on a schedule, then connect BigQuery to ChatGPT — either through a BigQuery MCP or via Codex with SQL queries. Instead of asking ChatGPT to pull raw Google Ads data, you let BigQuery aggregate into small, optimized tables, and ChatGPT only queries the summarized output. Scale problem solved.

When this makes sense: enterprise accounts with millions of impressions, agencies running multi-account analysis across 10+ clients, or any team already using BigQuery as a data warehouse. Porter loads Google Ads (and 25+ other sources) directly into BigQuery so you don’t have to build your own ETL.

Read the full BigQuery tutorial →

Connecting Google Ads to Codex

Most marketers lump ChatGPT and Codex together and miss the biggest advantage of the entire MCP ecosystem. They’re not the same tool — and the difference matters enormously once you start working with Google Ads data seriously.

ChatGPT is a chat interface. You ask a question, ChatGPT pulls live data through the MCP, answers, maybe builds a quick dashboard inside the conversation. Great for one-off analysis. The problem: everything is ephemeral. Want to refresh the dashboard tomorrow? You regenerate it from scratch. Want the same report every Monday? You re-ask the question every Monday.

Codex is ChatGPT running inside your computer’s terminal. Because it has access to your filesystem, runtime, and other developer tools, it doesn’t just answer questions — it can build real software. Persistent scripts, scheduled routines, HTML apps, internal dashboards, integrations that run 24/7 without your input. Once it’s connected to Porter’s MCP for Google Ads, a whole category of work becomes possible.

What Codex unlocks that ChatGPT alone cannot

This is where the MCP ecosystem pays off most. Because Codex can combine Porter’s MCP with other MCPs — Firecrawl for web scraping, Airtable for structured data, Notion for wikis, Vercel for deployment, Slack and Gmail for delivery — you’re no longer querying data. You’re building tools.

apps

Build your own Google Ads performance dashboard

Stack:Porter MCP + Vercel MCP (or Cloudflare Pages, Netlify) Feed Codex your Google Ads targets and goals — CPA goals, daily budgets, ROAS thresholds — and ask it to generate a custom ROI dashboard for each client. It builds the HTML, pulls live data, deploys to a URL. No Data Studio embed to break when the vendor changes pricing, no template constraints. The dashboard updates automatically because it queries Porter’s MCP on every page load.
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Best for:agencies that want white-label client dashboards without Looker or Data Studio dependencies.

visibility

Full competitor + performance monitoring

Stack:Porter MCP + Firecrawl MCP Combine your own Google Ads performance from Porter with competitor landing pages and live ads from the Google Ads Auction Insights scraped via Firecrawl. Codex stitches both into a weekly competitive intelligence report — your numbers next to their impression share and outranking share, with an LLM summary on top of what changed week over week. Runs on cron, lands in your inbox every Monday morning.

Best for:in-house teams that need market context, not just internal numbers.

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Internal marketing wiki with live metrics

Stack:Porter MCP + Airtable MCP (or Notion MCP) Use Airtable or Notion as the schema, Porter as the data source. Codex keeps every page populated with current spend, CPA, and ROAS for every account — no stale screenshots, no copy-paste from Excel. New hires read one wiki entry and have full context on a client’s account.

Best for:agencies and ops teams onboarding analysts or rotating account managers frequently.

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24/7 alerts on spend, CTR, and quality drops

Stack:Porter MCP + Slack MCP (or Gmail MCP) A Codex routine on cron pulls Google Ads via Porter, evaluates thresholds — CTR drops below 1%, daily spend spikes 2× the trailing average — and pushes Slack or Gmail alerts the moment something crosses the line. You stop checking dashboards reactively; the dashboard checks itself and tells you when to look.

Best for:any team that’s ever discovered a problem 48 hours too late because nobody opened the report.

Bottom line: ChatGPT is for quick questions and ad-hoc dashboards. Codex is for building apps, live dashboards, alerts, and actual tools — anything you want to run on its own without re-asking. Same Porter MCP URL works in both, so you don’t pick once and lock in.

Use cases — what you can actually do once Google Ads is connected to ChatGPT

Getting the connection right is half the battle. The real value shows up in what you do next — these are the jobs Porter users actually solve once Google Ads data is live inside ChatGPT.

Find where conversion lag is hiding your real ROAS

Google Ads attributes conversions back to the click date, so recent days keep filling in as offline imports, store visits, and view-through conversions land. A beginner reads yesterday's Conversions and Cost / Conv. as final and pauses a campaign that actually converts on a multi-day delay. ChatGPT with Porter MCP can pull Conversions, Conversion Value, Cost, and ROAS across a trailing window and flag where the most recent days are still maturing, so you don't kill a campaign on incomplete data.

chat_bubble“Compare conversions and ROAS for my last 7 days versus the 7 days before, and tell me which days still look like they're filling in”

chat_bubble“Which campaigns look like they're underperforming only because conversions haven't fully attributed yet?”

chat_bubble“Show me cost and conversions by day for the last two weeks so I can see the lag pattern”

Catch Search query waste that the campaign view hides

At the campaign level a Search campaign can look efficient while a chunk of spend leaks into irrelevant search terms that match broadly. The trap is that broad and phrase match keep matching new queries you never added, and the damage only shows at the search-term level. ChatGPT can break down Cost, Clicks, Conversions, and Cost / Conv. by search term and surface high-spend, zero-conversion queries that belong as negatives.

chat_bubble“Show me search terms that spent the most with zero conversions in the last 30 days”

chat_bubble“Which queries are draining budget but not converting, so I can add them as negatives?”

chat_bubble“Find search terms with high clicks but bad conversion rate this month”

Tell whether Performance Max is cannibalizing your branded Search

Performance Max blends Search, Shopping, Display, and YouTube inventory and reports as one channel, so its Conversions can quietly absorb branded searches that your Search campaigns would have won cheaply anyway. A beginner sees a great PMax ROAS and scales it without realizing part of that value was already-cheap brand traffic. ChatGPT can line up PMax against your branded Search campaign on Conversions, Conversion Value, and Cost so you can judge incremental versus borrowed credit.

chat_bubble“Compare my Performance Max campaign and my branded Search campaign on conversions, value, and cost this month”

chat_bubble“Is my branded Search volume dropping at the same time PMax conversions are climbing?”

chat_bubble“Break down conversions and ROAS by campaign type so I can see PMax versus Search”

Diagnose a CPA spike before you blame the bids

When Cost / Conv. jumps, the instinct is to lower bids, but the real driver is often a Search Impression Share or auction shift, a quality-score slide, or a landing experience change that tanked conversion rate. ChatGPT can decompose the CPA move into its parts using Cost, Clicks, CTR, Conversion Rate, and Average CPC across the same window, so you fix the actual cause instead of just starving the campaign.

chat_bubble“My cost per conversion went up this week, break it into whether it was CPC, CTR, or conversion rate”

chat_bubble“Which campaigns drove most of the CPA increase and what changed underneath them?”

chat_bubble“Show me average CPC and conversion rate trends for my top spenders over the last 30 days”

Spot budget-constrained winners that deserve more money

A campaign capped by its daily budget will show a healthy ROAS but a high lost impression share due to budget, meaning you're leaving cheap conversions on the table. Beginners scale the loudest campaign rather than the one that's profitable and throttled. ChatGPT can cross Conversions, ROAS, Cost, and budget signals to rank which campaigns are both efficient and constrained, the cleanest place to add spend.

chat_bubble“Which of my profitable campaigns are limited by budget and could take more spend?”

chat_bubble“Rank my campaigns by ROAS and tell me which ones are hitting their daily budget”

chat_bubble“Where would adding budget most likely buy me more conversions at my current CPA?”

Build a weekly account review without exporting a single CSV

The native UI makes you bounce between campaign, ad group, and keyword tabs and manually reconcile date ranges, which is why weekly reviews get skipped. ChatGPT with Porter MCP can assemble the whole picture, Cost, Conversions, Conversion Value, ROAS, CTR, and Average CPC, in plain language and call out the three things that actually moved. You read a summary instead of rebuilding a report.

chat_bubble“Give me a plain-English weekly review of my Google Ads account with the three biggest changes”

chat_bubble“Summarize spend, conversions, and ROAS this week versus last week by campaign”

chat_bubble“What are the most important things that changed in my account in the last 7 days?”

Google Ads fields and metrics you can query with ChatGPT

Before you start writing prompts, it helps to know what data is actually available. Porter MCP gives ChatGPT access to 1,042 Google Ads fields and metrics across every reporting level, plus breakdowns by audience, placement, device, and geography. And the same MCP URL also unlocks 25+ other sources — so ChatGPT can blend Google Ads with Meta Ads, GA4, Shopify, HubSpot and more in a single prompt.

Reporting levels (347 fields)

CampaignAd GroupAdKeywordAsset GroupConversion ActionBidding StrategyBudgetAudienceDeviceGeo TargetSearch Termand more — down to individual ad creative and keyword-level Quality Score components.

Visibility metrics (15 fields)

ImpressionsActive View measurable impressionsInvalid click rateOrganic ImpressionsAvg. Impression Frequency per Userand more.

Engagement metrics (87 fields)

ClicksCTRCostAvg. CPCAvg. CPMAvg. CPVEngagementsInteraction RateVideo view rateVideo views (25%50%75%100% quartiles)Gmail ForwardsGmail Savesand more.

Conversion metrics (97 fields)

ConversionsAll conv.Conv. rateCost / conv.Conv. value / costROASView-through conv.Cross-device conv.All conv. valueand granular conversion actions (PurchaseSignupLeadPhone Call LeadStore Visitetc.).

Efficiency — rates & costs (61 fields)

Target CPATarget ROASCampaign Bid StrategyBudget AmountBidding Strategy TypeMax Conv. Value Target ROASSearch Lost IS (budget)Search Lost IS (rank)and more.

Audience breakdowns (85 fields)

AgeGenderDeviceGeo Target (CityCountryStateMetro)Search keyword match typeSearch termNew vs Returning Customersand more.

Cross-channel sources (same URL)

Google AdsGoogle Analytics 4ShopifyHubSpotTikTok AdsLinkedIn AdsInstagramMailchimpKlaviyoActiveCampaignGoogle SheetsGoogle Search ConsoleGoogle Business ProfileFacebook InsightsFacebook Public Data+11 more

Prompts you can copy-paste today

For agencies & PPC managers

When you manage multiple client accounts and need standardized reporting, pacing checks, and fast performance summaries.

chat_bubble“Build me a one-paragraph client summary for this account covering spend, conversions, and ROAS this month versus last”

chat_bubble“Which of my managed accounts had the biggest CPA swings this week?”

chat_bubble“Flag any campaign where spend is up but conversions are flat so I can get ahead of the client call”

chat_bubble“Show me search-term waste across the account I can clean up before the monthly report”

chat_bubble“Compare this account's CTR and conversion rate against last quarter as a trend”

chat_bubble“Which campaigns are budget-limited right now and worth a budget conversation with the client?”

For B2B & lead-gen advertisers

When you run lead-gen campaigns and need to connect lead volume to lead quality and funnel performance.

chat_bubble“Which campaigns are driving the cheapest conversions and which are inflating my cost per lead?”

chat_bubble“Show me search terms bringing clicks but no form fills this month”

chat_bubble“Compare branded versus non-branded Search on conversions and cost per conversion”

chat_bubble“Is my Performance Max taking credit for leads my branded Search was already winning?”

chat_bubble“Break down conversions by campaign so I can see which ones feed real pipeline”

chat_bubble“Show me how cost per conversion trended over the last 30 days and where it spiked”

For DTC & e-commerce advertisers

When you track ROAS, purchase value, and the funnel from click to checkout across products and audiences.

chat_bubble“Show me ROAS and conversion value by campaign for the last 30 days”

chat_bubble“Which Shopping or PMax campaigns have the best return on ad spend right now?”

chat_bubble“Find products or campaigns where spend is climbing but conversion value isn't keeping up”

chat_bubble“Compare this week's ROAS to last week and tell me which days are still attributing”

chat_bubble“Which campaigns are profitable but capped by budget and could scale?”

chat_bubble“Show me average order value implied by conversion value over conversions by campaign”

For cross-channel & full-funnel teams

When you run on multiple platforms and need unified reporting and budget-allocation decisions across channels.

chat_bubble“Compare my Search, Shopping, and Performance Max campaigns on cost, conversions, and ROAS”

chat_bubble“Which campaign type is most efficient at driving conversions this month?”

chat_bubble“Show me where Display or YouTube spend is going and what it's converting”

chat_bubble“Give me a funnel read from impressions to clicks to conversions by campaign type”

chat_bubble“Which channel inside Google Ads has the worst cost per conversion right now?”

chat_bubble“Summarize total account spend and conversions split by campaign type this month”

How to use Codex for Google Ads without getting banned

The most common painful outcome with Google Ads is not a ban, it's acting on numbers that weren't finished yet. Conversions attribute back to the click date and keep filling in for days as offline conversions, store visits, and view-through actions import, so recent days almost always look worse than they'll end up. Marketers who pause campaigns or slash budgets based on the last day or two regularly cut campaigns that were actually converting fine on a delay, then have to rebuild momentum and re-enter the learning phase. The cost is lost conversions and wasted re-ramp time, not a disabled account.

Google's Ads API enforces a daily operations quota and per-request limits tied to your access tier rather than punishing reporting. Heavy or sloppy automation hits rate limits and gets throttled, and reads of partially-attributed recent data simply return incomplete numbers. The real failure modes here are quota exhaustion, sync lag on fresh dates, and acting on unsettled conversions, not account suspension.

The behaviors that actually put accounts at risk

Treating today's and yesterday's conversions as final. Recent days are still attributing. Reading Conversions or Cost / Conv. for the last day or two as settled numbers leads to pausing campaigns that convert on a delay. Always judge fresh dates as provisional.

Letting an agent push rapid budget or status changes unsupervised. Even though account bans aren't the risk here, a loop of automated edits can blow through API quota, fight the bidding algorithm's learning phase, and create changes you can't easily audit. Keep a human approving each write.

Comparing metrics across mismatched attribution or date settings. Pulling one campaign on one conversion window and another on a different range produces apples-to-oranges ROAS and CPA. Lock the window before you compare.

The safety protocol

Treat recent dates as provisional. For conversion-based metrics, assume the last several days are still maturing and label them as not-yet-final rather than acting on them.
Confirm before any write. Budget, bid, and pause changes go through explicit human confirmation. ChatGPT proposes, you approve, and the change is logged.
Lock the date range and attribution before comparing. Use the same window and conversion settings on both sides of any comparison so ROAS and CPA are actually comparable.
Respect API quota. Pull what you need in consolidated queries instead of hammering the API with many tiny calls, so you don't hit rate limits mid-analysis.
Reconcile against the native UI for big decisions. Before a major budget move, sanity-check the totals against the Google Ads interface so you're not acting on a sync gap or a metric definition mismatch.

What Porter MCP does differently: Porter MCP reads and analyzes your Google Ads data by default, pulling real metrics like Cost, Conversions, Conversion Value, ROAS, CTR, and Average CPC at the level you ask for. Where write actions are supported, they run through deterministic components with explicit human confirmation and backoff rather than free-form unsupervised edits, so a budget or status change only happens when you approve it. It does not browser-automate the Google Ads UI and does not fire rapid bursts of changes, which keeps you inside API quota and away from fighting the bidding algorithm.

How do I connect Google Ads to ChatGPT?

You connect through the Porter Metrics MCP. You add Porter as a connector in ChatGPT, sign in with the Google account that has access to your Google Ads, and authorize it. From then on you can ask ChatGPT questions about your account in plain language and it pulls the data through Porter.

Is this free? Do I need a paid ChatGPT plan?

Using custom connectors and MCP tools inside ChatGPT requires a paid ChatGPT plan, and Porter Metrics has its own subscription. We won't quote a price here since plans change, but budget for both a paid ChatGPT tier and a Porter plan.

Can I really use ChatGPT for Google Ads marketing work?

Yes. Once connected, ChatGPT can read your live Google Ads metrics and help you analyze spend, conversions, ROAS, search-term waste, and CPA trends in plain language, instead of you clicking through the native tabs and exporting CSVs.

Does this include related data like Shopping and Performance Max?

Yes. Google Ads reporting covers Search, Shopping, Display, YouTube, and Performance Max campaigns within the same account, so you can compare campaign types on cost, conversions, and value.

What's the difference between ad data and organic data here?

This connector covers paid Google Ads only, your campaigns, spend, and conversions. It does not include organic Google Search rankings or Search Console data. Those live in a separate connector.

Will using this get my Google Ads account banned?

Connecting for reporting and analysis does not put your account at risk. Google Ads reporting through the API is a normal, supported use. The thing to be careful with is letting automation make rapid unsupervised changes, which Porter avoids by requiring your confirmation on any write.

How much does it cost to run?

There's no per-query charge from Google for pulling your own reporting data within quota. Your cost is your ChatGPT plan plus your Porter Metrics subscription. We won't invent a figure here.

Is my data safe?

You authorize access with your own Google login through Porter's connector, and you can revoke that access at any time. ChatGPT reads the data to answer your questions; it doesn't get your password.

Should I use ChatGPT or Codex for this?

For asking questions about your account and getting summaries, regular ChatGPT with the Porter connector is what you want. Codex is OpenAI's coding-focused agent, useful if you're building scripts or automation around the data, not for everyday reporting conversations.

Can ChatGPT actually change my campaigns, like pause them or change budgets?

Google Ads supports write actions, so it's technically possible to push changes like pausing a campaign or adjusting a budget. Through Porter those run with explicit human confirmation, so nothing changes until you approve it. For most people the day-to-day use is read and analysis.

How fresh is the data?

It's close to live for spend and clicks, but conversion-based metrics for the most recent days keep filling in as attribution settles. Treat the last several days as provisional rather than final.

Are there rate limits I should know about?

Google's Ads API has quotas tied to your access tier, so very heavy or rapid querying can get throttled. Porter pulls data in consolidated queries to stay within limits, so normal analysis won't hit them.

How is this different from Supermetrics or Funnel?

Supermetrics and Funnel are built to pipe data into spreadsheets and dashboards. The Porter MCP approach lets you converse with your Google Ads data directly inside ChatGPT and get answers and analysis, not just a refreshed table you still have to interpret yourself.

Why do the numbers differ from what I see in the Google Ads dashboard?

Usually it's the date range, the attribution window, or recent-day conversions still maturing. The native UI may also default to a different conversion setting. Lock the same window and attribution on both sides and the numbers line up. For big decisions, sanity-check against the UI.

Ready to chat with your Google Ads?

Open ChatGPT, add the Porter connector, and ask your first question. If you don’t have Porter yet, start a free trial and connect your Google Ads account — you’ll be chatting with your campaigns in under five minutes.

rocket_launchStart free Porter trial open_in_newOpen ChatGPT