Model Context Protocol specialists
Newer tools change quickly, so it helps to work with someone who has already shipped the pattern you are buying.
We prototype the risky integration first, then sort out auth, data contracts, evaluation, and monitoring before spending time on polish.
If that sounds like your situation, Arcode is set up for 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. You see progress on the critical path every week.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. Nothing here waits on a handover between separate teams.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. On MCP development projects we favour practical architecture over trendy defaults.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. The work for teams in the USA stays tied to the outcome you asked for.
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 USA
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying US startups and enterprises hiring for shipping speed and applied AI. 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
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
Lengju Deildin
Realtime frontend · GraphQL
Live football league experience with sockets, GraphQL, and YouTube stream widgets.
Automated league app built at Stellar Stack with live scores, widgets, and stream integrations for higher fan engagement.
- · Realtime score updates
- · YouTube live widgets
- · GraphQL data layer
- · Automated league data views
React · GraphQL · Apollo · WebSockets · Firebase
Working with teams in USA
US startups and enterprises hiring for shipping speed and applied AI. Work is remote-first (US time zones), with written updates you can read in your own time. We usually collaborate in English.
How we work with USA teams
US engagements run on partial overlap: our afternoon is your morning. That is enough for a daily sync window with East Coast teams and a scheduled call with West Coast teams, with the rest handled in writing.
What USA clients usually need
US work is mostly seed-to-Series-A products that need to ship before the next raise, plus established companies adding AI features to software that already has users.
Contracts, data, and compliance
We invoice in USD and work under US-style contractor agreements with IP assignment. For healthcare and finance we scope compliance (HIPAA, SOC 2 evidence) into the build rather than bolting it on afterwards.
