Model Context Protocol specialists
Specialist work falls apart when it never leaves the demo stage. Anything in production still needs auth, data handling, monitoring, and an interface people can use.
Specialist features sit behind clear interfaces, so your core product stays stable while new capability gets added.
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 San Francisco 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 San Francisco
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying SF Bay Area expecting modern stacks and AI fluency. 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
Happy Kids Dental
Frontend · CMS
Pediatric dental site with services, patient resources, and appointment-focused UX.
Code Band clinic product using Next.js, Tailwind, Redux Toolkit, Video.js, and Strapi for content and scheduling flows.
- · Pediatric service pages
- · Patient resource content
- · Appointment scheduling UX
- · Strapi-managed content
Next.js · Tailwind · Redux Toolkit · Strapi · Video.js
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
Working with teams in San Francisco
SF Bay Area expecting modern stacks and AI fluency. We work with clients in San Francisco remotely and keep overlapping hours in PST/PDT. We usually collaborate in English.
How we work with San Francisco teams
San Francisco is on PT, which is the widest gap we work across. We hold one fixed call in your morning and run everything else in writing, so the time difference costs you a day at most on decisions.
What San Francisco clients usually need
Bay Area briefs are the most AI-heavy we see: agents with real tool access, RAG over internal knowledge, MCP servers connecting models to existing systems, and evaluation harnesses to prove any of it works.
Contracts, data, and compliance
Teams here expect modern defaults, so we work in TypeScript, ship through CI, and keep infrastructure reproducible. Expect direct technical conversation with whoever is writing the code.
