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MCP server development

MCP server developmentAn isometric drawing of an MCP server between an AI app and your systems. On the left a person asks a laptop. In the middle a sign-in gate, a cabinet with one drawer per tool (lookup_order, open_ticket, list_tickets) and a printer that logs each call. On the right your API and a database. A lookup travels all the way through; opening a ticket is refused at the cabinet until writes are allowed.the ai sidemcp serveryour systemslookup_orderopen_ticketlist_ticketsapi1234567

Claude and ChatGPT can use your systems, and you decide what they touch.

In short

If you want Claude or ChatGPT to look something up in your own system, or open a ticket in it, you need an MCP server in between. That's what this service is. We're Zenoware, a small studio in Auckland, and we've built them for products of our own as well as for clients here in New Zealand and overseas. Most go on top of an API you already have. You'd get sign-in, per-person permissions and a log of every call. The first call is free.

What you get

  • One server covers every MCP client

  • A tool that gets bad input says so, plainly

  • People sign in as themselves; we log each call

How it runs

  1. 01

    Agree the limits

    We'd begin by sitting down with you to agree what agents can read and change.

  2. 02

    Write the tools

    Writing the tools comes next, over HTTP (or stdio, if it only runs on a laptop).

  3. 03

    Test with real clients

    Once your real systems are wired in, we try it in Claude and ChatGPT.

  4. 04

    Ship

    Then it ships, with monitoring and a short guide for your developers.

Who you'll work with

JP Caparas

JP Caparas

Founder and lead engineer

Thirteen years of principal engineering, including development lead at Public Trust. OpenAI Codex and Devin ambassador in New Zealand. You talk to the person who writes the code.

About the team

Questions

What is an MCP server?

It's a small service that sits between an AI app and your systems. Claude or ChatGPT connects, sees a list of tools you've described (say, look up an order, or open a ticket) and calls them when someone asks. MCP, the Model Context Protocol, is an open standard Anthropic published in November 2024. OpenAI and Google adopted it in 2025.

What is the difference between an MCP server and an API?

Mostly in who reads it. A developer reads your API docs once and then writes code. A model reads the tool descriptions every time, and decides from those alone whether to call anything, so the wording matters more than you'd expect. The MCP server nearly always sits in front of an existing API rather than replacing it.

How do you secure an MCP server?

Use OAuth, so each person signs in and the agent can only do what they could. Validate inputs, rate-limit, and log every call along with its arguments (you'll want that log the first time someone asks why it did something). We also ship read-only tools first and add writes later, once you've seen how it behaves.

How long does it take to build an MCP server?

About five weeks on our standard plan. Week one is requirements and architecture. Weeks two and three build the core server, week four is integration and testing, and in week five it goes to production with docs.

Tell us what isn't working.

The first call is free, and we'll tell you straight whether we're the right people for it.

Start a project