Model Context Protocol specialists
Deep skills without product context tend to produce fragile integrations. The specialist work has to connect to real user flows.
We document the prompts, tools, schemas, and day-to-day runbooks so your team can run the system after we hand it over.
We work best with teams adopting agentic AI tooling who want a partner that ships. Custom MCP servers that connect AI agents to your tools, data, and workflows.
What you get
- Custom MCP server development
- Tool-calling integrations
- Secure agent access patterns
- Cursor and Claude-ready tooling
- Milestone pricing agreed after the consult
- Written scope before the build starts
- No retainer unless you ask for one
How engagement works
What moves the price on MCP development is integrations, content volume, compliance, and how quickly you need it. We estimate once we have seen the brief rather than quoting a blind package.
- 01
Discover
Goals, constraints, data sources, and success metrics, all settled before we touch architecture or prompts. Nothing here waits on a handover between separate teams.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. On MCP development projects we favour practical architecture over trendy defaults.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. The work for remote and worldwide teams stays tied to the outcome you asked for.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. You see progress on the critical path every week.
How we build it, and why
The stack is chosen per project, not applied from a template. For MCP developer work these are the defaults, and the reason each one is on the list.
- MCP
- the Model Context Protocol, so your tools plug into Claude, Cursor, and other agent clients without a custom adapter for each
- TypeScript
- types across the whole stack, which catches the class of bug that only shows up in production
- Node.js
- one language across the stack, so context does not get lost at the boundary
- Claude
- long-context reasoning and reliable tool calling for agent work
- OpenAI
- a second model provider, so a single vendor's outage or price change is not your problem
What the first weeks look like
- Week 1
Spike the risky part
We build the thinnest possible version of custom mcp server development against your real data. If it is going to be a problem, it is better to know in week one than week six.
- Weeks 2-3
Harden the integration
Auth, rate limits, error paths, and the data contract. This is the work that separates a demo from something you can leave running.
- Weeks 4-6
Wire it into the product
The MCP development stops being a standalone service and becomes a feature people use, with the interface and permissions that implies.
- Ongoing
Evaluate and tune
Behaviour gets measured against cases you care about, and we tune from that rather than from impressions.
Weighing up your options
There are three realistic ways to get this built. Each is the right answer for someone.
A solo freelancer
Cheapest per hour and fine for a contained task. The risk on MCP development is breadth — one person covering design, backend, infrastructure, and launch usually means one of them is weak, and there is no cover when they are unavailable.
An in-house hire
A permanent engineer is the right call once the MCP development is continuous rather than a project. Before that point you are paying a salary, recruiting for months, and carrying the risk that the first hire is the wrong shape for the problem.
Arcode
A small senior team. The people who scope the MCP development write the code, you get weekly demos instead of status decks, and the engagement ends when the thing is live and handed over.
Work we have shipped
Note Assist
AI product · Next.js · Speech
AI meeting assistant with live speech-to-text, ChatGPT chat, and Firebase auth for transcription workflows.
Freelance AI product built with Next.js, Firebase, AssemblyAI, and ChatGPT for live meeting transcription and realtime chat around the transcript.
- · Live speech-to-text transcription
- · Realtime chat over meeting notes
- · Firebase authentication
- · AI-assisted follow-up on transcripts
Next.js · Firebase · AssemblyAI · ChatGPT · TypeScript
Vigorant
Frontend · Accessibility
Accessible web app with reusable components, Redux Toolkit state, and Strapi integration.
Code Band product built with React, Next.js, Tailwind, and Redux Toolkit, focused on accessibility and maintainable UI patterns.
- · Accessibility-first UI
- · Reusable component system
- · Efficient Redux Toolkit logic
- · Strapi-backed content
Next.js · React · Tailwind · Redux Toolkit · Strapi
Quickee UI Library
Design system · Tailwind
Tailwind component library for React and Next.js with reusable UI patterns inspired by Tailwind UI.
Code Band component kit providing a variety of production-ready Tailwind components with Redux-friendly patterns for React and Next.js apps.
- · Reusable Tailwind components
- · React and Next.js ready
- · Consistent interaction patterns
- · Faster UI assembly across projects
React · Next.js · Tailwind · Redux
Where we work
International clients across US, UK, EU, Middle East, and Asia. We work remote-first, so the time zone matters less than keeping updates clear and regular. We usually collaborate in English.
