What Is an MCP Gateway, and Why Should MSPs Care?
MCP gateways are newer than they sound. The protocol they’re built on came out in late 2024, and the tools themselves started showing up in
The category is moving fast, and the language is still catching up. But for MSPs, they’re shaping up to be a real game-changer, and it’s worth understanding before the next wave of vendor conversations starts landing in your inbox.
What Does “MCP” Stand For?
MCP stands for Model Context Protocol. It’s an open standard, published by Anthropic in late 2024, that lets AI assistants talk to external tools in a consistent way. Open standard means no single company owns it. Anyone can build to it, which is part of why the category has grown so fast.
Before MCP, every connection between an AI assistant and a business tool was a custom build. If you wanted Claude to read your PSA, someone had to wire that up. If you wanted ChatGPT to do the same thing, someone had to wire it up again, differently. Multiply that by every tool in your stack and every AI assistant your team might use, and you get the situation most MSPs are in right now: AI on one side, a stack of tools on the other, and no clean way to connect them.
MCP changes that by giving the AI assistant and the tool a common language. One standard, one way to connect, no custom build per pair.
If you’ve ever appreciated the fact that any USB cable fits any USB port, you already understand the value MCP brings. Before USB, every printer, keyboard, and external drive had its own connector. After USB, there was one shape and one standard, helping every peripheral connect the same way. MCP does that for AI tool connections.
What’s a Gateway?
MCP makes connections possible. A gateway makes them safe, controlled, and observable.
In theory, an AI assistant could connect directly to every tool that supports MCP. That works fine for one person on a laptop tinkering with their own stuff. It falls apart fast in a business. You’d have credentials scattered across AI clients, no record of what was accessed, no way to control which users can do what, and no central place to manage any of it.
A gateway solves that by sitting in the middle. It handles four things:
- Authentication. Who is the person asking?
- Credentials. Which tools can this person reach, and how do we connect to them safely?
- Permissions. What is this person allowed to do once they’re connected?
- Audit. What did they actually do, and when?
The AI assistant sees one secure endpoint. The business sees one controlled, observable path to every tool.
How Does an MCP Gateway Help MSPs specifically?
Here’s where this matters more for MSPs than almost anyone else.
A typical MSP runs more tools across more environments than most businesses its size. PSA, RMM, documentation, M365, security stack, billing, and then all of that multiplied across every client you manage. Hand-wiring AI into that landscape isn’t realistic. Even if it were, the audit and access-control needs of a multi-tenant environment go well beyond what a one-off integration can provide.
It doesn’t matter which AI assistant the tech happens to be using—a gateway is the only model that fits the shape of an MSP’s actual stack:
- one controlled path
- per-user permissions
- per-client isolation
- a single audit trail that covers every tool call across every system
A couple of examples of what that looks like in practice …
A tech asks their AI assistant to summarize this morning’s tickets and flag anything past SLA. The gateway authenticates them, checks they’re allowed to read the PSA, makes the call, logs it, and returns the answer. The tech does in 30 seconds what used to take 20 minutes of scrolling.
Or the same tech asks to assemble a quarterly review for a specific client. The gateway lets them reach into the PSA, RMM, M365, and billing for that client only, pulls the data together, and logs every call. What used to be a two-hour exercise across six tabs becomes a single question.
Conduit is one example of this connectivity in action: an MCP gateway built for MSPs, by an MSP. But the broader point holds no matter which gateway an MSP eventually chooses: the gateway model is the only one that maps cleanly onto how the work actually gets done.
What Does This Mean for Your MSP?
You don’t need to become an MCP expert. You just need to recognize the shape of the problem so you can make a clear-headed decision about how your shop handles AI access.
A few practical takeaways:
- If your team is already using AI on client work (and they almost certainly are), a gateway is how you turn the lights on without turning AI off.
- If you’ve been thinking about AI as a project to build later, consider that a gateway gives you value today without a project at all.
- If you’re worried about audit, access control, and consistency across techs, those aren’t three separate problems. They’re the problem a gateway solves.
One to Watch
For MSPs in particular, MCP gateways are a clean fit: every tool, every team, one place to manage it all.
If you’d like to see what this looks like for your shop, book a 30-minute Zoom or come hang out in our Discord. No pitch, no pressure.