MCP gives compatible AI applications a common way to discover tools and context. Your systems still need clear interfaces, identities, and permission boundaries.
An agent is only as useful as the systems it can reach.
An assistant may understand a request to check an order, but it still needs a reliable way to look up that order. Without a connected tool, it can only explain a process or ask someone else to complete it.
Model Context Protocol, or MCP, standardises how compatible AI applications discover and interact with capabilities exposed by a server. A server can present tools for actions, resources for context, and prompts where supported. This reduces the need for a different custom connector for every client.
MCP usually builds on your APIs.
An API exposes the operations and data of an application. An MCP server can wrap selected API operations and describe them as tools an AI client can discover. For example, a catalogue API might support tools to search products and check availability.
That does not mean every endpoint should become a tool. A useful integration presents a small, intentional set of capabilities with clear names, descriptions, and input schemas. A focused tool such as ‘prepare purchase request’ can be easier to validate than a broad tool that accepts arbitrary instructions.
Design permissions around the user and the action.
A model choosing a tool is not the same as a user being authorised to run it. The integration must resolve identity, validate arguments, and apply permissions in the application layer. A user who cannot access a record in the source system should not gain access through an assistant.
Separate read operations, draft creation, and consequential actions. A tool can prepare a change for approval without being allowed to submit it. Credentials belong in the integration’s controlled configuration, not in model prompts or shared conversation history.
- Expose only the operations the workflow needs.
- Preserve user and tenant access boundaries.
- Make actions auditable and handle duplicate requests.
- Put approval gates before consequential changes.
Check the clients you actually plan to use.
A protocol is not a promise that every client supports every feature. Transport, authentication, protocol version, and capability support vary. Validate the specific clients and deployment model in your scope.
A local development tool and a shared remote service have different identity and operating requirements. Document supported clients, configuration, timeouts, rate limits, and error behaviour so the integration remains maintainable as the surrounding tools evolve.
Build an MCP interface when reuse is valuable.
MCP is useful when several compatible clients or agents need access to the same carefully scoped business capabilities. A direct API integration can still be the simplest choice for one application with a narrow, stable workflow.
Start by identifying the real task, its source of truth, the required actions, and the identity under which they run. Then choose the integration interface. The goal is useful, controlled access to your systems, with a clear owner and a path for maintenance.