Google DV360 to ChatGPT in 2026: 4 free ways to connect

boltTL;DR

To connect Google DV360 to ChatGPT:

1. Sign up free at portermetrics.com and connect your Google DV360 account with your Google account.
2. 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 DV360 advertisers with no usage limits on ChatGPT’s free plan. No credit card required.

What makes Porter different:

• 812+ Google DV360 fields and metrics, and the only MCP that includes attribution coverage in the same connection.
• Universal Google DV360 MCP. hosted white-label dashboards and client portals, competitor tracking with creative analysis, idea validation with Google Trends and keyword data. Your whole Google DV360 operation runs from one chat.

Connect Google DV360 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 DV360.

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 DV360 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.

The full setup takes under 5 minutes and breaks into three moves: connect Google DV360 to Porter, point ChatGPT at the Porter MCP, and ask your first question.

1. Connect your Google DV360 data to Porter

Porter sits between Google’s Display & Video 360 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. In Porter, click Create → pick ChatGPT as the destination → select Google DV360 as the source → sign in with Google to grant access to your advertisers.

Select your advertisers. Choose the Google DV360 advertisers you want ChatGPT to query. When you select multiple advertisers under a single connection, Porter automatically blends their data together so you can query them as one.

Optional: enable automatic BigQuery storage if you’re connecting multiple advertisers 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 DV360 data on demand in any conversation.

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

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

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

Pick Add custom connector from the dropdown that appears.

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.

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 DV360 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:

For a full catalogue of copy-paste prompts organized by use case (performance, viewability, budget, agency, B2B, e-commerce, cross-channel), jump to the prompts section below.

Alternative ways to connect Google DV360 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 DV360 data in front of ChatGPT, though. The most common alternatives are Google DV360’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 DV360’s direct API — Talk to Google’s Display & Video 360 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 advertisers or agencies running multi-advertiser 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:

1. Open the Porter Metrics app page in ChatGPT (or search “Porter Metrics” in the apps gallery).
2. Click Connect and sign in with the same account you use in Porter.
3. Authorize it and ask your first Google DV360 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 DV360’s direct API

If you’re building a product around Google DV360 — or you’re a developer who’d rather own every layer of the integration — the most direct path is talking to Google’s Display & Video 360 API yourself, or — where it exists — Google DV360’s own official MCP. Google doesn’t ship an official DV360 MCP yet, so going direct means writing API calls yourself in Codex or your own scripts. 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 DV360’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 Google 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 DV360 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 DV360 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 DV360 into a Sheet, then let ChatGPT read the Sheet. You can automate the Google DV360 → Sheets pipeline with Porter so it refreshes daily, or do one-off CSV exports from Google DV360’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.

Read the full Sheets tutorial → (no specific tutorial exists for Google DV360 at this time)

Via Google BigQuery (for scale)

This is the path most people overlook — and it’s the one that saves you when your Google DV360 advertiser gets serious. A single large advertiser or an agency managing 10+ advertisers 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 DV360 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 DV360 data, you let BigQuery aggregate into small, optimized tables, and ChatGPT only queries the summarized output. Scale problem solved.

When this makes sense: enterprise advertisers with millions of impressions, agencies running multi-advertiser analysis across 10+ clients, or any team already using BigQuery as a data warehouse. Porter loads Google DV360 (and 25+ other sources) directly into BigQuery so you don’t have to build your own ETL.

Read the full BigQuery tutorial →

Connecting Google DV360 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 DV360 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 DV360, 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.

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 DV360 is connected to ChatGPT

Getting the connection right is half the battle. The real value shows up in what you do next. Here are the use cases Porter users build around their Google DV360 data — from simple Q&A to full client-facing workflows.

1. Chat and ask questions directly

The simplest use case — and still the one 80% of marketers start with. Open ChatGPT, ask a question, get an answer grounded in live data.

It’s the fastest way to replace a daily DV360 native UI check-in. But chat is table stakes — the interesting use cases come next.

2. Blend Google DV360 with your revenue data (Stripe, HubSpot, Shopify)

This is where a 360° view gets real. When you connect Google DV360 and your revenue source (Stripe for SaaS, HubSpot CRM for B2B, Shopify for e-commerce), ChatGPT can map programmatic campaigns to actual closed-won deals or purchases — using UTMs, campaign names, and timestamps — and give you attribution that no platform-side number can.

ChatGPT handles the UTMs, campaign names, and timestamps mapping and joins. You get a client-ready attribution report that no single platform can generate on its own.

3. Automated alerts and notifications on Slack or Gmail

With Codex you can turn Google DV360 monitoring into a routine that runs on its own. Hook Porter’s MCP (for the data) together with a Slack or Gmail MCP (for delivery), then write a Codex scheduled task that pulls performance every morning and pings you only when something actually needs attention.

No dashboards, no daily check-ins. The report comes to you — and only when it matters.

4. Client-ready presentations with live data (Gamma, HTML, PDF)

A common agency pain: you send clients a Data Studio link, Looker breaks, the client panics — and you spend an hour explaining a broken dashboard. With ChatGPT you can build the presentation itself — as a Gamma deck, a custom HTML page, or a PDF — populated with live numbers each time.

The presentation becomes a delivery artifact you send to the client, not a dashboard that depends on another tool staying up. No broken iframe, no login prompts, just the content.

Google DV360 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 812 Google DV360 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 DV360 with Google Ads, GA4, Shopify, HubSpot and more in a single prompt.

Prompts you can copy-paste today

These prompts are organized by job: performance checks, programmatic deal & viewability analysis, client reporting, agencies managing multiple clients, e-commerce teams, and cross-channel blends. Copy any prompt, paste it into ChatGPT with Porter connected, and get live data back.

1. Performance checks

Quick health checks and rankings to spot what’s working and what needs attention.

2. Programmatic deal & viewability analysis

Deep-dive into viewability, frequency, reach, and video performance — the metrics that make or break programmatic campaigns.

3. Client reporting

Draft-ready summaries and tables you can drop into a client deck or email.

4. Prompts for agencies managing multiple clients

Multi-advertiser queries that help agencies stay on top of pacing, performance, and cross-client trends.

5. Prompts for e-commerce teams

Revenue-focused prompts that connect programmatic spend to actual sales outcomes.

6. Cross-channel prompts

Blend Google DV360 with other platforms in a single conversation for true attribution and comparison.

Limits, safety, and best practices for Google DV360 via ChatGPT

This quota collapse broke automated reporting pipelines for agencies running large DV360 accounts. A programmatic trader querying line-item pacing across 50+ advertisers could burn through the entire v3 daily quota in a single morning — not because they were doing anything wrong, but because Google deprecated v1 without warning and slashed v3 limits by two orders of magnitude. The cost wasn’t a ban; it was a silent, workflow-breaking throttle that left teams without fresh data during a campaign flight. This is the DV360 risk profile in a nutshell: the API is safe, but the guardrails are tight, and hitting them is easier than most marketers expect.

Google’s DV360 API enforcement is quota-based, not behavior-based. Google does not ban or suspend DV360 accounts because you used Claude, an MCP server, or any other API client. It throttles (HTTP 429 RESOURCE_EXHAUSTED) when a single Google Cloud project exceeds its daily or per-minute request quota — currently 1,440 requests per day and 60 requests per minute for API v3, with write requests capped at 30 per minute. Read-only access is safe and never triggers enforcement. Parallel API bursts, bulk write operations, or concurrent SDF downloads above 20 tasks per user are what trigger throttling. The system also returns 409 ABORTED when concurrent modifications collide. There is no “three strikes” policy, no account review, and no risk of losing DV360 access. The worst-case scenario is a temporary delay until the quota window resets.

The two ways to burn through your Google DV360 quota

After reviewing official docs and community threads, two patterns come up again and again.

1. Parallel API bursts that exhaust the 1,440 daily request quota. Querying every line item, creative, and insertion order across a large partner hierarchy in rapid succession — especially with multiple users or automated scripts — can burn the entire daily quota in minutes. When the quota is exhausted, all API calls return 429 RESOURCE_EXHAUSTED until midnight Pacific Time. The fix: batch requests, filter by date range and advertiser, and use SDF (Structured Data File) downloads for bulk data instead of iterative API calls. Source: Google DV360 API Quota Guide

2. Concurrent SDF downloads exceeding 20 tasks per user. The SDF API allows bulk download of campaign structures, but Google enforces a hard limit of 20 concurrent download tasks per user. Exceeding this threshold prevents new downloads from starting and can block other API operations tied to that user identity. This is especially dangerous when multiple team members or automation scripts share the same service account. The fix: queue SDF jobs serially or distribute them across separate service accounts. Source: Google DV360 API SDF Documentation

3. Treating DV360 reporting data as real-time when it has a 2–4 hour latency window. DV360 impression and engagement data is not real-time; it is typically available with a 2–4 hour delay (and sometimes next-day for certain verification metrics). Marketers who query “today’s” spend or pacing and make budget decisions based on it are working with stale data. This doesn’t trigger API enforcement, but it causes real financial damage — under-pacing insertion orders, overspending on poor-performing line items, or missing frequency-cap breaches. The fix: always query with a 4–6 hour lookback buffer, and use DV360’s native pacing alerts for same-day decisions rather than API polling. Source: Google DV360 Reporting Data Freshness

Both behaviors trigger quota throttling or stale-data decisions. If you want to use ChatGPT for Google DV360 safely, batch your queries, queue SDF downloads, and respect the 4-hour freshness buffer.

The 5-rule scaling protocol

Based on Google DV360’s documented quotas and the behaviors that have actually caused workflow breaks — not guesswork:

• Stay under 60 requests per minute and 1,440 per day. Google’s DV360 API v3 enforces 60 requests per minute and 1,440 requests per day per Cloud project, with write requests capped at 30 per minute. Exceeding these triggers 429 RESOURCE_EXHAUSTED and halts all API access until the quota window resets. Source: Google DV360 API Quota Guide Porter MCP enforces this automatically by batching queries and adding exponential backoff on 429 responses.

• Limit concurrent SDF downloads to under 20 per user. Google hard-caps SDF download tasks at 20 concurrent jobs per user. Exceeding this blocks new downloads and can deadlock shared service accounts. Source: Google DV360 SDF Documentation Porter MCP queues SDF requests serially and surfaces a clear error if the limit is approached.

• Use API v3 only — v1 and v2 are deprecated. Google deprecated DV360 API v1 and v2; the current base URL is https://displayvideo.googleapis.com/v3. Using legacy versions returns errors or outdated data schemas. Source: Google DV360 API Reference Porter MCP targets v3 exclusively and handles schema migrations automatically.

• Retry 409 ABORTED errors once after a few seconds, then stop. A 409 status means another process modified the same resource concurrently. Blind retry loops amplify quota burn. Google’s guidance is to wait briefly and retry once; if it fails again, surface the conflict to the user. Source: Google DV360 API Error Handling Porter MCP implements single retry with jittered backoff, then surfaces the error in Claude’s chat instead of looping.

• Query with a minimum 4-hour lookback to avoid stale-data decisions. DV360 reporting data has a 2–4 hour freshness delay (and up to next-day for some verification metrics). Querying “today” and acting on the results leads to under-pacing or overspend. Source: Google DV360 Data Freshness & Retention Porter MCP defaults date ranges to “last 7 days ending yesterday” and warns users when they request same-day data.

What Porter MCP does differently: it enforces these quota and freshness safeguards at the platform level so marketers don’t have to think about them. Porter’s DV360 MCP is read-only by default — no write operations, no risk of concurrent modification conflicts. It batches API requests behind the scenes to stay well under the 60 req/min and 1,440 req/day limits, and it implements exponential backoff with jitter on any 429 responses. SDF downloads are queued serially, never exceeding the 20 concurrent task ceiling. Date ranges default to “last 7 days ending yesterday” to avoid the 2–4 hour freshness gap, with an inline warning if a user asks for same-day data. Porter also uses the correct OAuth 2.0 scopes (display-video and display-video-user-management) and targets API v3 exclusively, eliminating deprecated-version errors. That’s the behavior Google’s automated quota systems handle gracefully — and why DV360 + Porter MCP is one of the safest API integrations in the marketing stack.

Frequently asked questions

Ready to chat with your Google DV360?

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 DV360 account — you’ll be chatting with your campaigns in under five minutes.

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