Central 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.
MCP integrations that lives in your stack, not on a vendor's roadmap. Shipped from Hong Kong Island.
Our goal is to give Central businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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
Without Kiwi Dynamics
With Kiwi Dynamics
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of MCP integrations runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Central businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How MCP integrations compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
What we keep seeing in Central.
- Central is Hong Kong's financial core, home to the regional headquarters of most major global banks - AI here has to meet a market built on precision, compliance and speed of execution.
- Hong Kong's stock exchange, the regional HQs of the world's biggest banks, and a dense wealth management and private banking sector all sit within a few blocks. Businesses here expect AI that's compliant-by-default and genuinely production-ready, not a pilot.
We work with teams across Central: Admiralty · Sheung Wan · IFC · Mid-Levels · Wan Chai.
Talk to us about this →
How we build MCP integrations for a Central team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Central business, so value lands before the build is finished. Connect Claude to your stack.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Central businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Central teams
Existing AI tools become 10x more useful with real business context. For Central teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
How fast could we have MCP integrations in production?
Eight to ten weeks for most Central businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for Central businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Has this actually shipped for a real Central?
Yes. Existing AI tools become 10x more useful with real business context. We'll share comparable engagements on the call.
What if our Central doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For MCP integrations specifically, we typically run that work on MCP, Claude, TypeScript, Vercel and assume messy starting conditions from day one.
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.