Tool calling is where AI agents move from conversation to action. That is also where risk increases. A tool can search a document, create a ticket, update a record, or trigger a workflow. Each action needs a clear contract.
Start by defining the tool boundary. What does the tool do? What inputs are allowed? What permissions are required? What is logged? What happens if the tool fails?
Use typed inputs and validation. Do not let free-form model output directly drive sensitive business actions. Validate parameters, restrict choices, and require approval for high-risk operations.
MCP can help organize tools and context, but it does not remove the need for governance. The architecture still needs identity, authorization, logging, and operational controls.
The safest tool design is boring in the right way: narrow actions, predictable inputs, explicit permissions, and visible audit history. This is how agent workflows become dependable enough for business systems.