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
- One studio accountable for the result
- Design and engineering on the same schedule
- Support available after launch
How engagement works
As your MCP developer, we run a shared backlog, design reviews, and engineering sprints, and you keep one point of contact throughout.
- 01
Discover
Goals, constraints, data sources, and success metrics, all settled before we touch architecture or prompts. The work for teams in North America stays tied to the outcome you asked for.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. You see progress on the critical path every week.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. Nothing here waits on a handover between separate teams.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. On MCP development projects we favour practical architecture over trendy defaults.
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.
A local agency in North America
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying US and Canadian startups shipping fast, plus established companies adding AI to products that already have users. rates for the whole team including the layers that never touch your MCP development, and a local shortlist is a small shortlist.
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
CRM Dashboard
Frontend · Analytics
Customer relationship dashboard with management workflows and data visualization on Next.js.
Freelance CRM surface for managing relationships and visualizing key metrics, deployed on Vercel.
- · CRM management views
- · Data visualization
- · Responsive dashboard layout
- · Vercel deployment
Next.js · React · Tailwind · Vercel
Agile IT Blog
Frontend · Astro
Performance-minded blog maintained in Astro with Markdown, Tailwind, and modular content integrations.
Stellar Stack content site where I improved performance and scalability across modular Astro components and data integrations.
- · Astro static content pipeline
- · Markdown-driven posts
- · Modular component structure
- · Performance and scalability pass
Astro · Markdown · Tailwind · SCSS
Working with teams in North America
US and Canadian startups shipping fast, plus established companies adding AI to products that already have users. Work is remote-first (ET to PT), with written updates you can read in your own time. We usually collaborate in English.
How we work with North America teams
North America spans ET to PT, roughly a three-hour band. We hold one standing call in the client's morning and cover everything else in writing, so the time difference costs at most a few hours on any decision.
What North America clients usually need
Most North American work is funded startups shipping an MVP against a deadline, plus companies bolting real AI features, agents, RAG, copilots, onto a product that already has paying users.
Contracts, data, and compliance
Contracts follow US or Canadian contractor norms with IP assignment. For regulated sectors, healthcare or finance, we scope the relevant compliance evidence, HIPAA or SOC 2, into the build plan from the first sprint rather than adding it before a raise.
