AI agent engineering is shifting from prompt refinement toward operational layers for skills, memory, MCP connections, credentials, behavioral evaluation, and execution. For web teams, these controls separate an impressive demo from a system that can be tested, governed, and maintained.

As MCP reaches real use, defining a tool is only the starting point. A server needs a clear contract, authorization boundaries, operational behavior, and accountable ownership.

Discussion of five MCP roadmap focus areas suggests an ecosystem working on platform concerns. For engineering teams, its value is not feature prediction but identifying assumptions that must remain flexible.