Not every AI integration needs an MCP server. Sometimes a direct API or SDK call is enough, and adding a protocol layer introduces complexity without solving a meaningful problem.
This talk will use an independent Java demonstration project to compare MCP-based and direct API integrations. Starting with the same task, I’ll explore what each approach requires and where the tradeoffs appear: authentication, deployment, latency, tool design, and maintenance.
The examples will examine when reuse across AI clients justifies an MCP server, when the resource model helps, and how to choose tool granularity. I’ll distinguish design expectations from observations gathered through the demonstration.
Attendees will leave with a practical checklist for deciding when to build an MCP server, when to use an existing one, and when a direct integration better fits their needs.