MCP Builds
One MCP server. Every major AI platform.
We build production MCP servers that wire your tools, data, and workflows into AI — built once to the open standard, so the same server plugs into Claude, ChatGPT, and Microsoft 365 Copilot.
Why It Matters
Your AI is only as useful as what it can reach.
Claude, ChatGPT, and Copilot are powerful out of the box — and blind to the systems your business actually runs on. Your CRM, your database, your internal apps, your product. Until the model can read and act on those, it is guessing.
The old answer was a custom integration per assistant: one for Claude, another for ChatGPT, a third for Copilot, each rebuilt every time a platform shipped a change. That is a treadmill, and it is why most of these projects stall.
MCP ended that. It is the open standard — created by Anthropic and now supported by every major platform — for connecting AI to your tools. Build one server to the standard and it works everywhere that speaks it.
Build once. Plug in everywhere.
One Build, Three Platforms
The same server, everywhere your team works.
MCP is generally available across all three major assistants. We build to the standard, then connect to the ones you use.
Claude (Anthropic)
Anthropic created MCP, and Claude was its first client. Your server plugs into the Claude apps, Claude Code, and the Claude API natively — no adapters, no glue code.
ChatGPT (OpenAI)
OpenAI adopted MCP across ChatGPT and its API. The same server connects through the Responses API and ChatGPT connectors, with read and write actions available in developer mode.
Microsoft 365 Copilot
MCP is generally available in Copilot. We ship your server as a Copilot Studio connector or a declarative agent via the M365 Agents Toolkit, so it shows up where your team already works.
What We Build
A real server. Not a demo.
Every build is production-grade from day one — designed, secured, deployed, and documented so your team can run it.
Tool & data design
We map which of your systems, APIs, and workflows belong inside AI — and design a clean, well-scoped tool catalog the model can actually use well.
Production MCP server
A real, hosted server built to the current MCP spec — not a demo. Structured tools, resources, and prompts, with sensible error handling and rate limits.
Secure auth & scopes
OAuth or token auth, least-privilege scopes per tool, and human approval gates on anything irreversible. The model gets only what it needs.
Platform connections
Wired into the platform you choose — Claude, ChatGPT, or Copilot — and ready to extend to the others from the same build.
Docs & handoff
Architecture notes, a tool reference, and a runbook so your team can operate and extend the server without us in the loop.
Safe by design
Isolated execution, audited access, and the same containment standard we run across every deployment. Your data stays where it belongs.
Packages
Build. Extend. Operate.
Start with one server on one platform. Add platforms and managed hosting as you grow.
MCP Build
You have tools, data, or a product you want available inside Claude, ChatGPT, or Copilot.
Multi-Platform
Your teams use more than one AI assistant and you want a single source of truth behind all of them.
Managed & Hosting
You want the server live and looked after without standing up the ops yourself.
Most teams start with a single MCP Build on the platform they use most. The same server extends to the others without a rebuild, so you are never re-paying to support a new assistant.
How It Works
From scope to live in weeks, not quarters.
Scope
Week 1We work out which tools, data, and actions belong inside AI, design the tool catalog, and agree on the platform target and security model.
Build
Weeks 2-4We build the MCP server to the current spec — tools, resources, prompts, auth, and scopes — and test it against real calls from the model, not a mock.
Connect
Weeks 4-5We wire the server into your chosen platform — Claude, ChatGPT, or Copilot — package it the way that platform expects, and validate the end-to-end flow.
Operate
OngoingWe deploy, document, and hand off. From there you run it yourself, or we host and maintain it under a managed plan as your systems evolve.
Who This Is For
You have systems worth connecting to AI.
FAQ
Common questions.
What is an MCP server?
MCP (Model Context Protocol) is the open standard for connecting AI models to your tools, data, and actions. An MCP server exposes your systems — APIs, databases, internal apps — as structured tools the AI can call. Because it is a standard, one server works across any AI platform that speaks MCP, instead of a separate one-off integration per assistant.
Does Microsoft 365 Copilot support MCP?
Yes. MCP is generally available in Microsoft Copilot. You can connect MCP servers through Copilot Studio or ship them as declarative agents built with the Microsoft 365 Agents Toolkit, and Microsoft now offers a wave of federated Copilot connectors built on MCP. So a server we build for you can run inside Copilot, not just Claude and ChatGPT.
Do we have to pick one AI platform?
No. That is the point of building to the standard. We build the server once and connect it to whichever platform you use today — Claude, ChatGPT, or Copilot — and the same server extends to the others without a rebuild. Choose one now, add the rest later.
What can an MCP server actually do?
Whatever your systems can do, exposed safely to the model. Read records from your database, look up a customer in your CRM, file a ticket, kick off a workflow, pull a report, update a record. We scope each tool, set least-privilege permissions, and put a human approval gate on anything that cannot be undone.
How much does it cost?
MCP builds start at $20,000 for a single production server connected to one platform. Connecting the same server to additional platforms and ongoing hosting and maintenance are scoped separately. We give you a fixed quote after a short scoping conversation.
How long does a build take?
Most single-server builds run three to five weeks from kickoff to handoff, depending on how many systems we are connecting and how clean their APIs are. We scope it precisely before we start so there are no surprises.
Is it secure?
Security is built in, not bolted on. The server runs with least-privilege scopes per tool, token or OAuth auth, isolated execution, audited access, and human approval gates on irreversible actions. It is the same containment standard we apply across every deployment.
Who owns the server when it is done?
You do. We build it, deploy it, document it, and hand it off with a runbook so your team can operate and extend it. If you would rather not run it yourself, we offer hosting and maintenance under a managed plan — but that is your choice, not a lock-in.
Put your systems inside your AI.
Book a call and we will scope the right MCP build for your tools and the platforms your team uses.