For users, MCP collapses integration to configuration: adding a server to Claude Code, Cursor, ChatGPT, or any compatible client is a line of config, after which the server's tools appear in the conversation like native abilities.
For products, it inverts the usual architecture. Instead of building an app that embeds an AI, you build a server that plugs into the AI surface people already use. The user keeps their client, their model choice, and their subscription; the server supplies the domain: its data, its actions, its rules.
ConvOps is built on this inversion: the entire engine (tasks, workflows, memory, pools, schedules, governance) is exposed as an MCP server, which is why the install is one line and there is nothing to migrate.