As agents evolve from quick tool calls to work that unfolds over hours or even days, MCP servers need to do more than expose tools. They need to teach agents what work they are suited for, how to sequence it, how to monitor progress, when to involve a human, and recognize when results have actually landed.
This talk presents a practical quality bar for MCP servers that support long-horizon agentic work. We'll discuss patterns for describing capabilities, guiding workflows, coordinating changes across services and validating outcomes, drawing on lessons from building effective MCP apps and plugins inside of ChatGPT and Codex. These patterns let us separate enduring design principles from changing protocol details, and discuss how today’s servers can adapt as tasks, triggers, resources, skills, and related MCP capabilities evolve.
