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MCP server development

MCP servers that let Claude, ChatGPT, Cursor and your own agents use your systems, with sign-in, permissions and a log of every call.

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In short

MCP server development means building the connector that lets AI apps like Claude, ChatGPT and Cursor use your own systems through the Model Context Protocol. We build servers for internal tools, databases and public APIs, read-only first, with sign-in and logs. One system usually takes one to four weeks, and we quote after a short call.

Let the AI your team already pays for reach your own systems.

Your team has Claude or ChatGPT open all day, and still copies data into it by hand. An MCP server fixes that. It describes your tools and data in one standard way, so any AI app that speaks the Model Context Protocol can look up an order, check a customer record or file a ticket.

We decide with you which actions are safe to hand over, start read-only, and put the same permission checks in front of the AI that you'd put in front of a new hire. Every call is logged. Write actions are added one at a time, with a confirmation step where it matters.

Is this for you?

You'll get the most out of this if

  • Your team pastes data from internal tools into ChatGPT or Claude every day
  • You want several AI tools and agents to share one connection to your systems
  • You have a product and want customers to use it from inside Claude or ChatGPT
  • Your security team needs to know exactly what the AI can read and change

Deliverables

What you walk away with

  1. 01

    An MCP server for your system

    Tools and resources for your API, database or SaaS, built on the official TypeScript or Python SDKs, hosted remotely or on your own machines.

  2. 02

    Sign-in and permissions

    OAuth so each person reaches only what they're allowed to, and read-only access until write actions are agreed.

  3. 03

    A log of every call

    Who asked, which tool ran, with what input and what came back. Useful for debugging, and for your auditors.

  4. 04

    Tested in the real clients

    Checked in Claude, ChatGPT, Cursor or your own agent, with a one-page guide your team can follow to connect.

Timeline

How the project runs

Typical timings for a first live version. We confirm yours in writing after discovery.

  1. Week 1

    Map

    Which systems, which actions, and which of them are safe to give an AI.

  2. Weeks 1 to 3

    Build

    The server, its tools and sign-in, tested against real tasks from your team.

  3. Weeks 3 to 4

    Pilot

    A small group connects first. We read the logs, then widen access.

  4. Ongoing

    Extend

    New tools and systems as your team finds more uses for it.

Usual stackMCP, TypeScript SDK, Python SDK, OAuth 2.1, Claude, ChatGPT, Cursor, Claude Agent SDK, OpenAI Agents SDK, Node.js, Python, Cloudflare Workers, Docker

Why a small studio

The person who scopes your project is the one who builds it, and the one who picks up when it breaks at 2am.

The founder is on your project
Hussain leads every build himself. You won't brief an account manager who briefs a developer who briefs someone else.
Three people, the output of ten
We build with Claude, Codex and our own agent tooling every day. A small senior team now covers what used to need a department.
We stay after launch
Evals before every release, a log of each AI decision, cost limits and someone on call. Month six matters more to us than demo day.
Your repo, your cloud
The code sits in your GitHub and runs in your AWS, GCP or Azure account from the first commit, on tools your next hire already knows.
Projects shipped
115
since 2014
Clients served
53
US, UK, EU, Middle East, APAC
Average rating
5.0
113 of 113 rated jobs
Years shipping software
18
the founder, since 2008

FAQ

Questions people ask

What is an MCP server?

A small service that describes your tools and data in a standard way, so any AI app that speaks MCP can use them. Build it once and it works in Claude, ChatGPT, Cursor and most agent frameworks.

Is it safe to give an AI access to our systems?

It's as safe as the permissions in front of it. We start read-only, make each person sign in, log every call and add write actions one at a time. We can also put the finished server through our AI security testing.

Should we build an MCP server or a normal API integration?

If one app calls one model, a direct integration is fine. If several AI tools or agents need the same systems, MCP saves you building the connection again for each of them.

How much does an MCP server cost?

We quote after a short call. A read-only server for one system is a small job. Several systems or strict permission rules take longer.

How long does it take?

One to four weeks. A read-only server for one system can be in your team's hands in the first week.

Keep exploring

Start here

Let's scope yours.

Send a few lines about the workflow or product. You'll hear back from Hussain within a working day with questions, a rough shape and a ballpark.

Book a free callhello@araneux.com