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.
Most people who reach this page are teams adopting agentic AI tooling. 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 Berlin 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 Berlin
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying Berlin startups hiring for shipping speed and modern stacks. 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
Dare To Donate
Mobile · React Native
Cross-platform blood donation app connecting donors and recipients with Firebase auth and realtime data.
Expo React Native app for donation matching with secure auth and cloud storage.
- · iOS and Android via Expo
- · Firebase auth and realtime DB
- · Donor/recipient flows
- · Secure cloud storage
React Native · Expo · Redux Toolkit · Firebase
Brain CMS
Frontend · Firebase · Analytics
Multi-module enterprise CMS with documents, calendars, video, and advanced analytics.
Content and operations system spanning enterprise modules with Firebase and rich media tooling.
- · Multi-module business domains
- · PDF and document management
- · Advanced charting suites
- · Calendar and media workflows
React · Redux Saga · Firebase · Chart.js · Video.js
Working with teams in Berlin
Berlin startups hiring for shipping speed and modern stacks. We work with clients in Berlin remotely and keep overlapping hours in CET/CEST. We usually collaborate in German/English.
How we work with Berlin teams
Berlin is three to four hours behind us, so there is a full shared afternoon. Berlin teams tend to move fast and decide in writing, which suits the way we run a backlog.
What Berlin clients usually need
Berlin is the most startup-weighted market we work in outside the US: early-stage products that need to be live before the next raise, and AI features added to products that already have traction.
Contracts, data, and compliance
We invoice in EUR with reverse-charge VAT. GDPR is scoped into the build, with EU-hosted data by default and a DPA provided as standard rather than on request.
