MCP integrations designed around the way a Wānaka team actually runs.

Our goal is to give Wānaka businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Wānaka sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default MCP integrations template would catch.

What MCP integrations actually does

Wire Claude, ChatGPT, or Gemini directly into your tools with the Model Context Protocol. Your team uses AI in their existing inbox, CRM, or chat - with your data, your permissions, your guardrails.

  • 01 Custom MCP servers for your CRM, ERP, or in-house tools
  • 02 Permission-aware so AI only sees what each user can
  • 03 Tool-call audit log for compliance
  • 04 Works with Claude Desktop, ChatGPT, Cursor, and more

Built on: MCP Claude TypeScript Vercel

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How MCP integrations compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Our field notes from Wānaka builds.

  • Wānaka has the boom-and-shoulder rhythm of a lifestyle town - AI here helps small teams handle big seasonal swings without burning out.
  • Tourism, hospitality, lifestyle property, and trades feeding constant builds. AI shines when it lets a small operator look like a big one.

We work with teams across Wānaka: Wānaka township · Albert Town · Hāwea · Cardrona · Lake Hāwea.

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How we build MCP integrations for a Wānaka team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Wānaka business, so value lands before the build is finished. Connect Claude to your stack.

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How the work runs

The outcome for Wānaka teams

The shape of the result for Wānaka teams: Existing AI tools become 10x more useful with real business context. Built on MCP, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

Try the calculator

*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

What's the realistic timeline for MCP integrations with a Wānaka?

Most Wānaka businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".

Is MCP integrations worth it for a smaller Wānaka?

Often, yes - and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.

Anyone else in this space using MCP integrations?

Plenty. Existing AI tools become 10x more useful with real business context. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.

What happens if we want to swap a vendor out later?

MCP integrations is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. MCP, Claude, TypeScript, Vercel are our defaults, but the build is intentionally portable.

Sketch this with us.

We'll map your real workflow before quoting anything.

Talk to us about this

Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.