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AI data leakage 8 min read

What is an MCP server, and what are you connecting to it?

Integrations between AI tools and your own systems now take a few clicks, often from the employee's own laptop. Here is what actually happens.

Admin reviewing an assistant's connected integrations
Quick answer

The Model Context Protocol is an open standard describing how an AI assistant talks to external systems. An MCP server is a small program that connects to your system on one side (mail, calendar, a database, an API) and tells the assistant which tools it may use on the other. It is why integrations suddenly became easy, and therefore why employees now build them without asking. What matters: who wrote the server, where it runs, which permissions it holds on your behalf, and whether that token ever expires.

01

MCP is an open standard for connecting assistants to systems

02

An MCP server translates between your system and the assistant's tools

03

The connection is often made by the user, with no procurement or review

04

Granted permissions are usually wider than the task requires

05

It is a supply chain: an MCP server is somebody else's code

An analyst wants their assistant to answer questions about sales figures. They find an MCP server for the data warehouse, paste a connection string into a config file, and within ten minutes the assistant can query the database.

No ticket was raised. No procurement decision was made. A connection now exists between an AI service and the system holding revenue data.

What MCP is

The Model Context Protocol is an open standard, introduced by Anthropic in November 2024, describing how an AI assistant talks to systems outside itself. The specification is public.

The problem it solves is real. Before MCP, every assistant-and-system pair needed its own integration: one for this assistant with that CRM, another for a different assistant with the same CRM. With a shared standard you build the integration once and any conforming assistant can use it.

That is the move USB made for peripherals, and the consequence is the same: the number of connections climbs because the barrier is gone.

What an MCP server does

An MCP server is a small program that speaks in two directions.

On the system side it connects to whatever you want to expose: a mailbox, a calendar, a database, an API, or simply files on a disk.

On the assistant side it advertises the available tools. Not as documentation for humans, but as a machine-readable description: this tool is called find_customer, it expects a name, it returns a customer record. The assistant reads that list and can then invoke the tools.

An important detail: the assistant decides when to call which tool. You ask for sales figures, and the model determines which calls that requires. That is exactly what makes an agent an agent.

Where it gets interesting

Not in the protocol. That is a specification, and a good one. It sits in what grows around it.

It is somebody else's code. An MCP server is a program you install that gains access on your behalf. That is a supply chain, with the same questions as any dependency. In July 2025, CVE-2025-6514 was published, a command injection flaw in mcp-remote, a widely used proxy with hundreds of thousands of downloads. Not unusual for young software, and a good reason to know what you are running. OWASP maintains an MCP security cheat sheet covering this ground.

Permissions exceed the task. Connecting frequently requests full access where read-only would have done. Easier for the builder, and wider than necessary.

Tokens do not expire. A granted token typically stays valid until somebody revokes it, including after the user changes their password. Short-lived scoped tokens are the recommendation; long-lived ones are the practice, because they cause less friction.

Nobody assessed it. The largest of the four. The connection was made by someone trying to work faster, which is how shadow AI always arrives.

Why this is the next wave

The first wave of shadow AI was a browser tab: somebody opened a chatbot and pasted something in. Unwelcome, and bounded by what that person pasted.

An MCP connection is a door. What is shared is not text but access, and that access persists after the employee goes home. What travels through it afterwards depends on what the assistant decides it needs.

On top of which, an assistant with integrations also reads external content, making it susceptible to instructions hidden in that content. See what is prompt injection.

What to put in place

  1. Know which exist. On managed machines you can see which MCP servers are installed. Without management this becomes asking, with an incomplete answer.
  2. Assess provenance. From the system vendor itself, or from an unfamiliar repository? The same distinction you apply to any dependency.
  3. Narrow permissions at connection time. Read where reading suffices. This is the moment it is possible, because nobody revisits it afterwards.
  4. Expire tokens. And make sure there is somewhere they can be revoked.
  5. Treat it as a vendor. The same questions as in approving an AI tool, because that is what it is.

The reason to look at this now rather than next year: connections are cheap to create and expensive to unwind. A tab you close. Granted access has to be revoked by someone, and first they have to know it exists.

FAQ

Common questions

What is MCP?

The Model Context Protocol, an open standard introduced by Anthropic in November 2024 describing how AI assistants can talk to external systems and tools. The goal is that you do not build a separate integration for every assistant-and-system combination.

What does an MCP server actually do?

It sits between the assistant and a system. On one side it connects to your mail, a database or an API. On the other it advertises to the assistant which tools are available and what each one does.

Why is this a risk?

Not because of the protocol, but because an MCP server is a program holding access on your behalf. Who wrote it, where it runs, which permissions it requests and whether tokens expire are all questions asked of a normal integration and often skipped here.

Do employees really set these up themselves?

Frequently, and that is the point. Installing an MCP server takes minutes and requires no procurement. That creates a connection between a business system and an AI tool that nobody assessed.

What should we check on an MCP integration?

Who built the server and whether it comes from a trusted source, where it runs, which permissions were granted and whether they can be narrowed, whether tokens expire, and whether the transport is encrypted. OWASP publishes a cheat sheet for this.