MCP server development that holds up in production.
I design, build, and deploy MCP servers — the secure bridges that let AI read and act inside the systems your business already runs. This page is for owners and operators who want one built. Mine run in production today, used daily by internal teams, and the AI tools your team already uses agree on the standard: Claude, ChatGPT, Gemini, and Microsoft Copilot all support MCP. Every build starts with the $4,500 operations audit, so the ROI case is on paper before I write a line of code.
Not sure what an MCP server is yet? Start with the business owner's guide → Free, and no form in front of it.
Charlotte, NC + remote · Your infrastructure · You own the code
One server per system. You own every one of them.
An MCP server is built once per system — one for the CRM, one for inventory, one for the books. Each build covers four things, and skips none of them.
Scoping: which systems earn a server
Not every system pays for one. We rank yours — CRM, ERP, inventory, accounting — by what an agent could actually do there, and build where the return is.
Permission design: read vs. write
Per system, we decide what the AI can read, what it can write, and what's off-limits — with logging where it matters. This is where I spend the time.
Deployed on your infrastructure
Your cloud, your accounts, your keys. Nothing routes through mine, and nothing depends on me staying in the picture.
Documentation and handoff
Code, docs, and training for the team that runs it. You own all of it. Support is available — never mandatory.
Your systems already have APIs, and the server is built on top of them, not instead of them. If you're weighing a plain API integration against a server, here's what's actually different between MCP and an API, and when you need which.
The last one I built is in production right now.
At a mid-market reverse logistics-tech company, the MCP server and agent tooling I built now carries 50+ internal users through their live inventory and truckload workflows — Python, on Google Cloud, every day.
MCP is young enough that a lot of what's for sale is demo work. Production is a different job: real permissions, real data, and internal users who notice by 9 a.m. when something breaks. That's the standard your server gets built to.
The code is the easy part. Deciding what not to expose is the job.
Wiring an AI into a CRM takes days. Deciding what it should be allowed to do there is the real work. The server is the gatekeeper — you decide per system what the AI can read, what it can write, and what's off-limits, and every action can be logged. Get that design wrong and you've handed a very fast intern the keys to every room.
One caution from the field: off-the-shelf MCP servers deserve the same scrutiny as any software you'd install. The ones I build run on your infrastructure, under your permissions — shaped to exactly what you allow, and nothing else.
That gatekeeper pattern is public code, not a pitch: mcp-gatehouse is my open-source library for permission tiers, approval gates, and audit logging in MCP servers. Read the code before you hire anyone — including me.
So is the testing: fieldtwin runs open-source twins of the Jobber and QuickBooks Online APIs, with an MCP server of its own, so integrations and agents get tested against a fake business before they touch real books. Five ways a Jobber and QuickBooks integration fails, and how to test each one →
One system at a time. Audit, design, build, handoff.
Audit — one week, $4,500
The operations audit maps your systems and finds where a server pays. The fee is credited toward your first build — and if it doesn't surface savings worth more than its cost, you don't pay.
Design
Which systems, which permissions, what the agents will do with them — and what done looks like, before a line of code gets written.
Build
A focused server is usually days to weeks of work, not months — typically part of a fixed-scope build sprint from $45,000, built alongside the agents that use it.
Handoff
Deployed on your infrastructure, documented, your team trained. If you want the builder to stay on, that's the fractional AI partner — an option, not a requirement.
What this engagement is not.
- A plugin install. An off-the-shelf connector exposes what its vendor chose. A built server exposes exactly what you allow — and nothing else.
- A chatbot. If all you need is answers from a manual, you don't need MCP — and I'll tell you that before you spend a dollar.
- Vendor lock-in. MCP is an open standard under neutral foundation governance. The servers you build are yours, and they work with any AI that speaks the protocol.
- A science project. The server ships wired into the workflows that run your business — alongside the agents that use it — or it doesn't ship.
Before you commission an MCP build.
What does MCP server development cost?
A focused server for one system is usually days to weeks of work, not months. It's typically part of a build sprint (fixed scope, from $45,000) that includes the agents that use it — and every engagement starts with the $4,500 operations audit, which tells you whether it's worth building at all.
Which systems can an MCP server connect to?
Anything with an API or a database — CRM, ERP, accounting, inventory, even the spreadsheet workflows. The server wraps what you already run; nothing gets ripped out or replaced.
Who maintains the MCP server after handoff?
You do — you own the code, the infrastructure, and the documentation, and your team gets trained to run it. If you'd rather have the builder stay on to maintain and harden it, that's what a fractional engagement is for. It's an option, not a dependency.
Does an MCP server work with ChatGPT, Claude, and Gemini?
Yes. MCP is an open standard — created by Anthropic, released in November 2024, and donated to the Agentic AI Foundation, a Linux Foundation fund, in December 2025. Claude, ChatGPT, Gemini, and Microsoft Copilot all support it natively, so the server you build works with any of them and keeps working when you switch.
Why hire an MCP developer instead of installing an off-the-shelf server?
Scrutiny and fit. Off-the-shelf MCP servers deserve the same scrutiny as any software you'd install — you're trusting someone else's decisions about what your AI can touch. A built server runs on your infrastructure, under permissions you set per system, with every action loggable. For systems that touch money or customer data, that difference is the job.
A note from Nick
From one operator to another.
If the work keeps outgrowing your team, your team is doing something right. The busywork grew with it, and that part can be fixed.
Before I wrote code, I built a sales company with 120+ reps on contract and 77 consistent producers. It taught me that a system only pays off when the people doing the work actually use it, so I build for the person who runs it every day, not for the demo.
We start by asking your team for their advice: where the week really goes, and what they'd fix first. The plan comes out of their answers, so it's already theirs when it ships.
Nick George · Charlotte, NC
What a client said
“His code was elegant and precise, and his communication was clear and prompt. … The task was extremely complex … Nicholas diligently worked, and implemented an impeccable solution.”
AI training from
NVIDIA · Google · Microsoft · AWS
5 credentials, each with a public verify link. Check them →
Until something connects your systems, your team is the connection.
Find out which of your systems earn a server.
That's what the audit is for: one week, $4,500, and you get the map — where an MCP server pays off in your operation, what the build costs, and what it returns. The fee is credited toward your first build. If it doesn't surface savings worth more than its cost, you don't pay.
Or read how the operations audit works →
New to MCP? Start with the business owner's guide →