I spend a lot of time asking questions about the business.
That is part of the job. The mistake is assuming every question needs someone else’s time.
Some are obvious: Where are we on ARR? What changed this month? Which accounts need attention? What should go into the next board discussion?
Others are smaller but still important. What am I missing? What trend is starting to form before it becomes a bigger issue? What would I ask next if I had finance, RevOps, and customer success sitting next to me all day?
Not every question is important enough to interrupt the team. In the past, getting answers usually meant waiting on reports, pulling data from different systems, or asking someone to stop what they were doing and go dig.
Maxio MCP has changed that for me. I can follow my curiosity, get oriented quickly, and decide what actually needs attention without creating more work for everyone else.
What Is Maxio MCP?
MCP, or Model Context Protocol, lets an AI client connect to a business system and work from live context instead of only what is pasted into a prompt.
Maxio MCP connects Maxio to AI clients in a secure, governed way. Depending on your setup and permissions, that can include contracts, customers, subscriptions, billing, invoices, and transactions.
That changes the workflow in a meaningful way. Instead of exporting data, stitching it together, and then trying to interpret it, I can ask a business question in plain language and get back something useful. For me, Maxio MCP is best for exploration, prioritization, and explanation. APIs are still the right choice when I need something deterministic and repeatable.
Workflow 1: Preparing for executive leadership meetings
One of the most common things I do is prepare for our monthly executive leadership team meeting.
Before, that meant pulling reports, reviewing the numbers, trying to spot patterns, and turning that into a discussion agenda. Now I can start with a much simpler ask in Claude: give me the ARR and customer summary month to date and year to date. From there, I ask for highlights, lowlights, and the issues I should be ready to discuss.
What I like about this workflow is that it helps me get past my own assumptions. I usually go into meetings with a view on what matters most. The model helps surface trends, changes, and blind spots I might not have prioritized on my own.
From there, I will often ask it to draft a note to my leadership team so they know what I’m coming into the meeting focused on. Sometimes I will also ask it to create a presentation framework from the same analysis.
If you want a good first use case, start here. Start with a recurring executive review. Ask what changed. Ask what deserves discussion. Then ask for the email or deck.
Workflow 2: Knowing which accounts need my attention
I’m on customer calls all the time, and I want to know where my attention actually matters. One prompt I use regularly is some version of: Which accounts show the most concerning signals right now, and can you pull briefs for them?
The brief part matters because I built a customer brief skill so I get a consistent format every time. I’ve already defined what I want to see: account snapshot, payment information, signals, risks, context, and recommended actions.
That means I get the kind of output I actually want as an executive, not every possible data point. I get where the account stands, what looks off, what follow-up is warranted, and what conversation I should probably have.
And if the brief shows me something that needs action, I can immediately ask for a draft email to the account owner, the team, or the customer. That tight loop from signal to action is what makes this useful.
Workflow 3: Using Maxio MCP on mobile when I want a fast answer
I also use Maxio MCP on mobile more than most people expect.
A lot of business questions do not show up when you are sitting at your desk, ready to run a formal analysis. Sometimes you just want a quick answer. What is going on with MRR? Should I dig into this account? Has something materially changed since the last time I looked?
That is where mobile is useful. I can ask a question quickly, follow up, and drill into account-level detail if I need to.
There is also a practical reporting detail worth understanding. Maxio MCP can use cached report logic for speed. If a recent report is still fresh, it may use that rather than rerun it. If it is stale, it can run it again. And if you want the latest available data, it helps to be explicit and ask for the most current report.
That is a small but important point: good MCP usage is not about being vague and hoping the model reads your mind. It is about being direct when precision matters.
Workflow 4: Building board materials faster
Board prep is another place where this becomes immediately useful.
A lot of leaders spend too much time building the first draft of a board narrative from scratch: pulling screenshots, cleaning up data, and trying to make materials presentable. That is not a great use of executive time.
I use a board-pack workflow that I have refined over time. I’ve already told the system what I like in a board pack, what I do not like, what structure I want, and what kind of story I’m trying to tell. So when I ask for it, I am not starting cold. I am asking for a first draft that already reflects my preferences.
Then I edit.
That part matters. I do not treat the output as final truth. I treat it as a strong first draft. If it includes a conclusion I do not agree with, I change it. If it interprets data in a way that is technically correct but not contextually useful, I refine it.
The point is not to hand over judgment. The point is to spend my time on the judgment and the story, not on manually building the raw materials.
Workflow 5: Building one-off dashboards and deeper analysis
One of the more useful applications is answering questions that matter but do not justify a full BI project.
Sometimes I want to explore product performance, GRR, NRR, account behavior, or a pattern I’m curious about. MCP plus Claude lets me build a one-off dashboard, iterate on the analysis, and decide whether it was simply exploratory or something worth standardizing.
That distinction matters.
Not every analysis needs to become a permanent dashboard. Some of it is throwaway. Some of it is just part of how leaders think through the business. But when something proves repeatable, that is when it makes sense to operationalize it.
The right balance is simple: explore first, standardize when it proves valuable.
Prompting, iteration, and validation
One of the most practical lessons I have learned is this: do not stop after the first bad answer.
I see people try one prompt, get a number they do not expect, and decide the whole thing does not work. The better move is to tell the model why it is wrong.
If I know the output should match a specific report, I say that. If needed, I will drop in the report URL, the report name, the report ID, or even a screenshot and ask why it is pulling something different. That usually gets me much farther than starting over.
I also like starting broad and then drilling deeper. Broad questions help surface useful paths. Then I tighten the prompt, add constraints, add thresholds, and specify the output format I want.
Validation matters even more when you start combining systems. If you are working across Maxio, Salesforce, call data, marketing attribution, or anything else, you need to stay anchored to the right source of truth for the question you are answering.
My rule of thumb is simple: be curious, but stay grounded.
Why Maxio MCP changes how I work as a CEO
The bigger shift is not that AI writes things for me.
It is that I do not need to choose between staying close to the business and protecting the team’s time.
I can ask more questions, explore more ideas, and move faster from raw data to a point of view. And when something matters, I can turn it into communication or action much faster than I could before.
It does not replace finance, RevOps, customer success, or analytics. It makes the interaction with those teams better. It helps me come in with sharper questions and a clearer point of view. And it lets the team spend less time packaging data and more time driving the business forward.
So where would I start?
I would not overcomplicate it. Pick one workflow you already care about. Set up the connector. Ask a real question. Refine the result. Save what works. Then build from there.
That is where the value starts.
I’m sharing these examples because they reflect a broader shift in how I think leaders can work: staying closer to the business, asking better questions, and moving more quickly from context to action.
I recently covered this in my session of our executive webinar series, AI in the C-Suite: How Maxio Leaders Make Faster Decisions with MCP and the on-demand recording goes deeper into how I use these workflows in practice. If you want to understand how we can support that shift, get a Maxio MCP demo here. And if you want to hear how other Maxio leaders are approaching it, you can also sign up for the rest of the executive webinar series, which includes sessions from our CFO and Head of Sales.
