What Is an MCP Gateway? The Control Point Between Your AI Assistants and Your Systems
An MCP gateway is a single entry point between your AI assistants and the tools they connect to. Instead of every employee wiring Claude, ChatGPT or Copilot to your systems one by one, the gateway holds the connections, decides who can reach what, and records what was called.
You do not need one while a few people are experimenting. You need one when AI use moves from enthusiasts to the whole company — because that is the point where nobody can say any more which tools are connected, who can reach them, or whether anyone is actually using them.
MCP in one paragraph
MCP, the Model Context Protocol, is the open standard that lets an AI assistant connect to other software: your CRM, your inbox, your file store, your own internal systems. Before it existed, every tool needed a custom integration for every assistant. Anthropic published it openly, the rest of the industry adopted it, and now a tool that speaks MCP works with any assistant that does. If you want the plain-language version with the setup steps, read what Claude connectors are and which one to set up first. This article is about what happens next: when it is not one person connecting one tool, but a company.
The problem a gateway solves
Do the arithmetic for a company of fifty. Each person uses one or two AI assistants. Each connects the handful of tools they need — CRM, email, the shared drive, the project tracker. That is easily three or four hundred individual connections, each set up by a different person, each holding its own login, none of them written down anywhere.
Nothing is wrong with any single connection. The trouble is the total:
- Nobody has an inventory. Ask which systems your AI tools can reach today and the honest answer at most companies is “we are not sure”.
- Access is set by whoever connected it. Some people gave read-only access, some gave write access, and it was nobody’s decision.
- Leavers keep their connections. Offboarding checklists were written before AI assistants held their own keys to company systems.
- Nothing is recorded. If a client asks what an AI did with their data, there is no log to answer from.
- Most of the team has nothing connected at all. The same sprawl that gives a few people too much access gives everyone else none, because setting it up was left to them.
That last point is the one that gets missed. Sprawl is not only a risk problem. It is the reason most companies see a handful of power users and a long tail of people who tried AI once and went back to copy-paste.
What an MCP gateway actually does
A gateway sits in the middle. Assistants connect to it; it connects to the tools. Every request passes through one place, which is what makes the rest possible.
| What it does | What that means | Why a leader cares |
|---|---|---|
| One entry point | Employees connect their assistant to the gateway once, instead of to every tool separately. | Setup stops being each person’s job, so it actually happens. |
| Access by role | Finance reaches the accounting system; sales reaches the CRM; nobody reaches what their role does not need. | The approved setup becomes the default rather than a policy nobody reads. |
| Credentials held centrally | The gateway holds the connection to each tool. Individuals do not each keep their own keys. | Offboarding is one switch, not a hunt. |
| Only approved tools exposed | An assistant sees the tools and actions you have allowed, and nothing else. | Read-only by default is enforced, not requested. |
| A record of what was called | Which assistant called which tool, on whose behalf, and when. | You can answer the question “what did the AI touch?”. |
| A view of what is used | Which connectors and tools are called, how often, by which teams. | You see where AI is actually doing work, not just where it is licensed. |
Gateway, registry, server: the three terms
You will meet all three in the same vendor conversation. They are different things.
An MCP server is the connector for one tool. It exposes that tool’s data and actions in the standard format — one for your CRM, another for your file store, another for an internal system your developers built.
An MCP registry is a catalogue of servers. The MCP project runs a public one listing servers that exist; companies also keep a private registry of the servers they have approved. A registry answers “what is available?”. It does not, on its own, control who uses what.
An MCP gateway is the control point in front of many servers. It answers “who may use which of these, and what happened when they did?”. In practice most gateways include a registry of approved servers, which is why the terms get blurred.
Server: one tool, plugged in. Registry: the list of what can be plugged in. Gateway: the switchboard that decides who gets connected to what, and keeps the log.
Do you need one yet?
Probably not if a small team uses one assistant with two or three connectors. The administrator controls in a business plan — switching connectors on for the organisation, restricting them to read-only — cover that stage well, and adding infrastructure before you have the habit is backwards.
You are past that stage when several of these are true:
- More than a couple of teams use AI assistants on real work every week.
- People use more than one assistant — Claude in one team, Copilot in another, ChatGPT somewhere else.
- You want AI to reach internal systems that have no off-the-shelf connector.
- You handle personal, financial or regulated data that assistants could touch.
- Someone — a client, an auditor, your board — will ask you to show what AI accessed.
- You cannot currently say which teams are using AI and which are not.
What to ask before you choose one
The market for MCP gateways is young and most products are sold on security features. These questions sort the options faster than a feature list.
| Ask | Why it matters |
|---|---|
| Where does it run, and where are the logs stored? | Some gateways are hosted by the vendor; others run in your own cloud or data centre. For European companies with data-residency requirements this is usually the first filter. |
| Which assistants does it work with? | If your teams use more than one, a gateway tied to a single assistant solves half the problem. |
| How does access map to our identity provider? | Roles should come from the directory you already manage, not a second list someone has to keep in sync. |
| How is a new tool added? | If adding a connector takes a ticket and three weeks, teams will route around it and the sprawl returns. |
| What does it show about use, not just risk? | A gateway that only reports blocked requests tells you what went wrong. One that shows who uses which tools tells you whether the investment is working. |
Security is only half the story
Most vendors in this category lead with control: see everything, block what is risky, stop shadow AI. That is real, and for regulated industries it is often what gets the budget approved.
But the bigger payoff is the other direction. A gateway that makes the approved tools available to everyone by default is how the eighty per cent of the team who would never have configured a connector themselves get access at all. And because every call passes through one place, it is also the first time most companies can see adoption as it happens: which teams use AI, for what, and which connectors earn their place. We cover the numbers worth tracking in how to measure AI adoption.
Where to start
You do not start with a product. You start with four decisions, and they are the same ones whether you end up with a gateway or not.
- Take an inventory. Ask each team which tools they have connected to which assistant. The answer is usually more than anyone expected.
- Decide the approved list. Which tools may be connected, for which roles.
- Make read-only the default. Grant write access per tool, where the time saved is obvious.
- Name one owner. Someone who adds and removes connectors and answers “am I allowed to connect this?” in one message.
With those four in place, the question of whether you need a gateway usually answers itself: either the plan’s own admin controls are enough, or they clearly are not.
Mapping what your teams have connected, deciding the approved list and getting the whole team onto it is the work we do in Deployed Partner. If you are earlier than that, a Deployed Kickstart gets every team connected to the right tools in a single session.
Frequently asked questions
What is an MCP gateway?
An MCP gateway is a single entry point between AI assistants such as Claude, ChatGPT or Copilot and the business tools they connect to through the Model Context Protocol. Instead of each employee connecting their assistant to every tool separately, assistants connect to the gateway once. The gateway holds the connections to the tools, decides who can reach which tool based on their role, and records which tool was called, by whom and when.
What is the difference between an MCP gateway and an MCP server?
An MCP server is the connector for one tool: it exposes that tool’s data and actions in the standard MCP format. An MCP gateway sits in front of many servers and controls access to all of them. A company typically has many MCP servers, one per tool it connects, and at most one gateway that decides who may use which of them and keeps a record of what happened.
What is an MCP registry?
An MCP registry is a catalogue of MCP servers. The MCP project runs a public registry of servers that exist, and companies often keep a private registry of the servers they have approved for use. A registry answers what is available, but on its own it does not control who uses what. Most MCP gateways include a registry of approved servers, which is why the two terms are often blurred.
Does a small company need an MCP gateway?
Usually not while a small team uses one AI assistant with a few connectors. At that stage the administrator controls in a business plan, such as switching connectors on for the organisation and keeping them read-only, are enough. A gateway becomes worth it when several teams use AI on real work, when people use more than one assistant, when AI needs to reach internal systems without an off-the-shelf connector, or when someone will ask you to show what AI accessed.
Is an MCP gateway a security tool?
Partly. Most MCP gateways are sold on security features: one place to control access, keep credentials, enforce read-only defaults and log what AI tools touch. But the larger payoff is often adoption. A gateway that makes the approved tools available to everyone by default gives access to the people who would never have configured a connector themselves, and because every call passes through one place it shows which teams actually use AI and for what.
Can an MCP gateway run on our own infrastructure?
Many can. Some MCP gateways are hosted by the vendor, while others can run in your own cloud account or data centre. For organisations with data-residency requirements, especially in Europe, where the gateway runs and where its logs are stored are usually the first two questions to ask a vendor.
Found this useful? Send it to someone who needs it.