Making your business services available through MCP

What is MCP, and what would you be making available?

Model Context Protocol, or MCP, is a standard for connecting AI applications to information and actions in other software. An MCP server describes the capabilities your business makes available; a compatible AI application connects as a client. The server is software, so this does not necessarily mean buying a physical machine.

For a business offering services, the opportunity is to let an authorized customer or partner use those capabilities from their own AI assistant. A supplier could offer stock checks. A logistics company could offer shipment status. A maintenance provider could accept a service request. You choose the operations and the information each one returns.

This is different from publishing a page about your services. A page explains what you do; an MCP connection can let another application request information or perform a defined action. It still needs working connections to your underlying systems. It does not replace your customer database, pricing rules, or booking process.

Where it could help customers do business with you

Consider an equipment rental company whose commercial customers regularly call to check availability. A proposed MCP service could let a customer’s assistant ask for suitable equipment, collection locations, and availability for a particular date. The customer could compare the returned options without a member of your team answering each preliminary question.

The next operation might create a reservation request with a reference number. We would keep that distinct from a confirmed booking: your system would still check account eligibility, current availability, and any required deposit or approval. The assistant should never turn “available when checked” into a promise that equipment has been reserved.

This is most useful when customers or partners already have a compatible AI workflow and repeatedly need information from you. Before building, ask a few of them how they would use it. Publishing an MCP server does not automatically put your business into AI recommendations, improve search rankings, or bring an audience to the service.

The risks are the permissions behind the conversation

A customer must only see their own account details and agreed prices. Signing in is not enough: each request needs checks against the account, records, and action being requested. The MCP authorization specification describes authorization for HTTP connections, but your application still has to enforce its business rules.

A booking, cancellation, or order change also needs protection against mistakes and retries. If a connection drops after an order is created, repeating the request must not create a second order. A cancellation should identify the exact booking and pass the required approval before anything changes. Describing an operation as “read only” is a hint to the AI client, not a security boundary.

There is also a new service to operate. Credentials can be mishandled, endpoints can be abused, and upstream systems can be unavailable. We would define request limits, useful error responses, access revocation, and logs that support investigation without collecting unnecessary customer information. A public endpoint should never mean unrestricted access to private business records.

What AIR Interactive would build and take responsibility for

We would start with the customer task and check whether an MCP connection is justified. If an existing integration already solves it, that may be the better choice. If MCP is appropriate, we would agree a small set of operations, the intended AI clients, the source systems, and the permissions before writing the server.

For the rental example, the first release could cover availability and reservation requests, with confirmation staying in your existing process. We would build the system connections, return clear results, and test expired access, unavailable equipment, duplicate requests, and attempts to read another customer’s records. Testing would include the actual AI applications your customers intend to use.

The handover should explain how to connect, who can approve access, how to investigate a failed request, and who maintains the integration when systems change. Ongoing support would be agreed as part of the scope. Our role is to make the service usable and supportable, with evidence that it respects the boundaries your business needs.

If you are considering this, bring us one repeated customer request and the system that currently handles it. We can assess whether it is a sensible first service to make available through MCP.