Make.com already has Google Ads modules.
So why use a Google Ads MCP server at all?
Because the native Google Ads nodes are best when you already know the exact step you want: run this report, upload this conversion, add this item, call this endpoint.
That is useful.
But it is still a module-by-module workflow.
Google Ads MCP adds a different layer: an AI agent can understand the PPC task, choose the right Google Ads action, pull the right data, summarize the result, and pass the next step back into your Make scenario.
So the difference is not:
“Make nodes vs MCP.”
It is: fixed modules for known steps vs an AI-operable PPC layer for flexible workflows.
For example, a native node can help you run a campaign report.
An MCP-connected agent can help you ask:
Pull campaign performance, find campaigns with rising CPA, check search terms for wasted spend, export the supporting data, and send me the three issues worth reviewing first.That is the gap.
Native nodes are great building blocks.
Google Ads MCP gives Make a PPC operator’s toolkit.
What is Google Ads MCP for Make.com?
Google Ads MCP lets Make connect to a Google Ads MCP server and use structured Google Ads actions inside AI agents or scenarios.
Make already has native Google Ads modules, including areas like campaign management, reporting, conversions, lead forms, and customer match.
Those are useful when your workflow is predictable.
Use this module. Fill these fields. Pass the result forward.
MCP is different.
With MCP, the AI agent can work from the PPC task itself.
It can decide whether it needs a campaign report, search terms report, hygiene check, PMax report, change history lookup, or CSV export.
In simple terms:
Make handles the workflow.
The AI agent handles the reasoning.
HireOtto handles the Google Ads actions.
You can still use both.
Use case | Native Google Ads nodes | Google Ads MCP with HireOtto |
|---|---|---|
Fixed report pull | Good | Good |
Conversion upload | Good | Not the main use case |
Lead form workflows | Good | Not the main use case |
PPC task from plain English | Limited | Strong |
Multi-step account review | Manual to wire | Strong |
Search terms analysis | Manual to build | Strong |
PMax performance review | Depends on modules | Strong |
CSV + summary together | Manual to wire | Built into workflows |
AI decides next report/action | No | Yes |
Write actions with PPC context | Limited/fixed | Strong |
Use native nodes for fixed, predictable steps.
Use HireOtto’s MCP server when the workflow needs PPC context, analysis, and flexible action selection.
That is where this gets interesting.
Why Make.com is different from ChatGPT or Claude
ChatGPT and Claude are conversational workspaces.
Make is an automation workspace. That changes the use case.
In ChatGPT, you might ask:
Review this account and tell me what needs attention.In Make, you might build:
Every Monday morning, pull campaign performance, summarize issues, export CSV, and send a Slack update.Same Google Ads layer. Different operating model.
Chat tools are great for interactive work. Make is great for repeatable work.
The best agencies will use both. Because no serious operator wants to manually pull the same report every Monday until retirement.
Why connect Google Ads to Make.com?
Because many Google Ads tasks are recurring.
Not all PPC work needs a human to start it.
A human should review decisions.
But the first pull, sort, group, and summarize step can often be automated.
Make.com plus HireOtto is useful for:
weekly performance summaries,
search terms review workflows,
daily pacing checks,
CSV export workflows,
agency account monitoring,
PMax performance reviews,
hygiene checks,
change history snapshots,
client reporting prep.
The real benefit is not “AI magic.”
It is removing the tiny manual handoffs that slow every agency down.
Download this. Upload there. Rename file. Paste summary. Send update. Question your life choices.
Make handles the plumbing.
HireOtto gives the plumbing useful Google Ads actions.
How to connect HireOtto to Make.com
Make supports MCP servers through Make AI Agents and Scenarios.
With AI Agents, you can add an MCP server below the system prompt.
With Scenarios, you can add an MCP node.
The nice part: HireOtto is already listed as a supported Google Ads server inside Make.
So you do not need to paste the server URL manually.
Step 1: Add the MCP server
Open the MCP modal in Make.
Add a name.
Then choose “select a server.”
Search for:
GoogleAdsSelect the pre-configured HireOtto server.
Click Add.
Step 2: Complete the first connection
A Google sign-in window will open. Approve the prompt.
This confirms Make can reach HireOtto as a remote MCP server.
Step 3: Authenticate Google Ads
Ask the agent:
Connect Google Adsor:
Authenticate Google AdsHireOtto will return a Google Ads authentication link.
Open it, grant access, and select the accounts you want to use.
When the auth page says you are done, return to Make.
Step 4: Verify the connection
Run a simple prompt:
List my accessible accountsor:
List campaigns for <account id>If Make returns your accounts or campaigns, the connection works.
What can you automate with Google Ads MCP in Make?
Start with workflows that are repetitive, bounded, and easy to review.
That gives you leverage without creating chaos.
Here are the best starting points.
Workflow 1: Weekly campaign performance report
Use this when you send recurring updates to yourself, your team, or clients.
Trigger
Every Monday at 9 AM.
MCP action
Pull campaign performance for the last 7 or 30 days.
AI step
Summarize:
top campaigns by spend,
campaigns with rising CPA,
campaigns with low conversion volume,
campaigns with improving efficiency,
recommended next checks.
Output
Send a Slack message, email, Notion update, or Google Sheet row.
Prompt
For customer ID <account id>, pull campaign performance for the last 7 days.
Summarize spend, conversions, CPA, conversion rate, and ROAS where available.
Flag campaigns that need attention.
Do not recommend budget changes unless the data clearly supports them.This is a good first automation because it does not make changes.
It creates awareness.
Awareness is underrated. Especially before coffee.
Workflow 2: Search terms waste finder
Search terms review is one of the most automatable “first pass” tasks.
The human should approve negatives.
But the machine can find the obvious suspects.
Trigger
Weekly.
MCP action
Pull search terms for the last 7 or 30 days.
AI step
Group queries by issue:
low intent,
irrelevant product/service,
competitor ambiguity,
research intent,
job-seeker intent,
location mismatch.
Output
Send a review list.
Prompt
For customer ID <account id>, review search terms from the last 30 days.
Find queries with spend and no conversions.
Group them by likely reason.
Suggest negative keyword candidates for review only.
Do not apply negatives.
Export the full list to CSV.That last line matters.
A CSV gives you a clean review artifact.
Useful for client approvals. Also useful for your future self, who will not remember why “free template” was blocked.
Workflow 3: Daily ops audit
This is useful for agencies managing many accounts.
The goal is not to deeply audit every account daily.
The goal is to surface issues early.
Trigger
Every weekday morning.
MCP action
Run a daily ops audit.
AI step
Summarize pacing flags, spend anomalies, and wasteful search term patterns.
Output
Send a priority list to Slack or email.
Prompt
Run a daily Google Ads ops audit for customer ID <account id>.
Summarize pacing concerns, spend anomalies, and search term waste.
Rank issues by urgency.
Do not make account changes.This is where Make becomes more than a connector.
It becomes the morning radar.
Not the pilot. The radar.
Still useful. Much cheaper than panic.
Workflow 4: PMax account monitor
PMax needs regular inspection.
But not every inspection needs to start manually.
Trigger
Weekly or twice per week.
MCP action
Pull PMax campaign, asset group, and asset performance.
AI step
Flag weak asset groups, spend concentration, and performance changes.
Output
Send a summary to Slack, Notion, or email.
Prompt
For customer ID <account id>, analyze Performance Max performance for the last 30 days.
Break down performance by campaign and asset group.
Flag weak asset groups, spend concentration, and conversion efficiency issues.
Suggest what to inspect next. Do not make changes.For PMax, automation should surface questions.
Humans should still make the calls.
The black box is already black enough. No need to add a blindfold.
Workflow 5: Change history snapshot
This is useful when multiple people touch accounts.
Especially agencies.
Trigger
Daily or weekly.
MCP action
Pull change history.
AI step
Summarize material changes.
Output
Send an internal note.
Prompt
For customer ID <account id>, review recent Google Ads change history.
Summarize important changes by campaign, change type, and likely impact.
Separate routine changes from changes that deserve review.This gives teams memory.
And in agency life, memory is not a nice-to-have.
It is how you avoid “who changed this?” archaeology.
Workflow 6: Client-ready reporting prep
This does not need to send the final client email automatically.
It can prepare the draft.
Trigger
Every Friday afternoon or month-end.
MCP action
Pull account, campaign, search terms, and device reports.
AI step
Summarize performance in plain English.
Output
Create a draft email, Google Doc, Notion page, or Slack post for review.
Prompt
For customer ID <account id>, prepare a client reporting summary for the last 30 days.
Include performance highlights, issues, search term insights, and next actions.
Keep it concise and client-friendly.
Export supporting data to CSV.
Do not send anything externally.That last line is important.
Automation should prepare the cannon.
You still decide whether to fire it.
Make.com vs Google Ads UI
Make is not replacing the Google Ads UI.
It is replacing repeated movement between tools.
Job | Better in Make + MCP | Better in Google Ads UI |
|---|---|---|
Scheduled reports | Yes | No |
Repeated account checks | Yes | No |
Slack/email alerts | Yes | No |
CSV export workflows | Yes | Sometimes |
Search terms first pass | Yes | Sometimes |
Visual investigation | No | Yes |
Final manual review | Sometimes | Yes |
Complex one-off changes | Sometimes | Yes |
What should you not automate first?
Do not start with high-risk write actions.
Avoid fully automated changes to:
budgets,
bidding strategies,
campaign status,
negative keywords,
geo targeting,
PMax assets,
account-level settings.
Can these be handled through HireOtto? Yes.
Should your first Make scenario change budgets while you sleep?
Please do not build the PPC equivalent of a Roomba with scissors.
Start with read-only workflows. Then move to “draft changes for approval.”
Then consider limited write workflows for narrow, reversible tasks.
A good first Make workflow
Build this:
Weekly Google Ads account pulse
Trigger every Monday.
Pull campaign performance for the last 7 days.
Pull search terms with spend and no conversions.
Summarize issues.
Export supporting CSVs.
Send the summary to Slack or email.
Include “no changes made” in the message.
Prompt:
For customer ID <account id>, prepare a weekly Google Ads pulse.
Pull campaign performance and search terms for the last 7 days.
Flag campaigns with high spend, low conversions, or CPA above target.
Find search terms with spend and no conversions.
Group issues by urgency.
Export supporting data to CSV.
Do not make any changes.This gives you immediate value without operational risk.
Once that works, clone it for more accounts.
That is where agencies start feeling the compounding effect.
Agency use case: monitor many accounts without living in the dashboard
For agencies, the big win is not one report.
It is repeatability.
If you manage 20 accounts, a single weekly check becomes 20 tiny workflows.
If each one requires logging in, filtering, exporting, scanning, and summarizing, the dashboard becomes your second office.
And unlike your actual office, it has more dropdowns.
With Make and HireOtto, you can standardize the first pass:
every account gets checked,
every output follows the same structure,
every issue gets routed,
every report starts from current account data.
This is how small teams start behaving like larger ops teams.
Not by hiring more clickers.
By designing better loops.
FAQ
Does Make.com support HireOtto?
Yes. Make already includes HireOtto as a supported Google Ads MCP server. Search for GoogleAds in the MCP server dropdown.
Do I need to paste the HireOtto server URL in Make?
Usually no. The HireOtto Google Ads server is pre-configured inside Make’s supported server list.
Can I use HireOtto in Make AI Agents?
Yes. In AI Agents, you can add an MCP server below the system prompt.
Can I use HireOtto in Make Scenarios?
Yes. In Scenarios, use an MCP node.
Can Make change my Google Ads campaigns through HireOtto?
Yes, if you configure a workflow that uses write actions and approve the required access. Start with read-only workflows first.
What is the safest first automation?
A weekly performance summary or search terms review. Both create value without changing the account.
Is this useful for freelancers?
Yes. Freelancers can automate reporting prep, search terms reviews, and recurring account checks.
Is this useful for agencies?
Very. Agencies get the biggest benefit when they standardize workflows across many accounts.
Final thought
Make.com is not where you go to chat with your ad account.
It is where you go to make repeated work happen without repeated effort.
HireOtto gives Make the Google Ads action layer it needs.
So the question is not: “Can AI manage Google Ads?”
The better question is: Which parts of Google Ads work should stop waiting for you to click first?
Start there. That is where the leverage is
About Me
I’m Suyash – badminton junkie, ex‑GroupM ad‑ops grunt, first marketer at a B2B SaaS startup, and creator of Hiretto: Google Ads MCP Server.
My mission: think, so you can click less.
Let’s build leverage together.