video1.0<iframe src="https://www.loom.com/embed/6db425d5f5e34866b8c2cc444ad6456c" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/6db425d5f5e34866b8c2cc444ad6456c-0e802bd87cca7847.gif116.967This Loom explains how to run an AI-assisted workflow that combines research with asset creation and manages a content library through MCP. The speaker says you can use conversation context such as call notes, a gong transcript, or CRM data as the brief for building assets, and even ask the assistant to research a company like AWS and their priorities before creating materials such as a landing page using a template. It also shows how the assistant can search, upload, tag, and organize existing library items through MCP, with examples like tagging a Snowflake case study with Data Cloud and Enterprise. The main value is turning MCP from convenience into a core go-to-market workflow.