We've worked with enough operators in Cyberport to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any MCP integrations project is sit with your team for a day before we propose anything.
For Cyberport operators who want a working pilot in weeks, not a year-long programme.
Our goal is to give Cyberport 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 Cyberport 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's different about doing this work in Cyberport.
- Cyberport is Hong Kong's dedicated tech and fintech precinct, purpose-built to house the city's startup and digital economy - AI here is judged by founders and engineers, not procurement committees.
- A government-backed tech park concentrating fintech, AI and digital media startups alongside venture capital and accelerator programs. Businesses here expect AI built with real technical rigor, since many of them build software themselves.
We work with teams across Cyberport: Pok Fu Lam · Telegraph Bay · Wah Fu · Aberdeen.
Talk to us about this →
How we build MCP integrations for a Cyberport team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Cyberport 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 Cyberport 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 Cyberport teams
Existing AI tools become 10x more useful with real business context. For Cyberport 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
What's a typical engagement length for Cyberport businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
What's the realistic outcome for Cyberport businesses?
Existing AI tools become 10x more useful with real business context. We don't promise tenfold lifts because we don't see them outside of marketing decks.
Can you work with our existing systems?
Yes. The default MCP integrations stack we reach for is MCP, Claude, TypeScript, Vercel, but we'll bend it around whatever you already run - Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
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.