Tag: mcp

Motivation protocols could let agents exchange goals, constraints, progress, and evidence across systems, but safe interoperability requires typed semantics, provenance, permission boundaries, and user-visible ownership.

MCP can connect motivational AI to calendars, tasks, health data, and workflows, but useful interoperability depends on scoped authorization, trusted servers, and action-aware UX.

Permissions for tool-using agents work like game rules: they define the action space, limit blast radius, and make safe autonomy possible without asking users to approve every trivial step.