Asana MCP
Give AI agents governed hands on your Asana workspace via MCP
A Model Context Protocol integration lets autonomous AI agents read and act on your Asana workspace through a controlled, permissioned interface. Agents can create and update tasks, query project state, manage assignments and due dates, and post updates — all within guardrails we define. This turns Asana from a place people update into a system agents help run.
Agents open tasks and subtasks, set custom fields, assign owners, and adjust due dates as project conditions change.
Agents read tasks, sections, portfolios, and custom fields to answer status questions and identify blockers or overdue work.
Agents add comments, attach context, and post project status updates so stakeholders stay informed without manual reporting.
Agents move tasks between sections, apply tags, and set dependencies to keep pipelines flowing to the right stage and owner.
An agent queries a portfolio each morning, summarizes what shipped, what slipped, and what is blocked, and posts a clean digest to stakeholders — no one assembles it by hand.
An agent reads new request-form submissions, classifies them, sets priority and custom fields, and assigns the right owner so every request lands in the pipeline correctly within minutes.
When a campaign metric shifts or a build ships, an agent opens or closes the matching Asana task and comments the context, keeping work and reality in sync across tools.
We scope the MCP connection to specific projects and actions and set approval gates, so agents operate only within the permissions you grant and sensitive changes still get human sign-off.
Yes. Every agent action lands as a normal Asana task, comment, or field change with attribution, so the full trail lives in your workspace history.
Any MCP-compatible client, including Claude and the custom agents we build, can connect through the same standardized protocol, so you are not locked into one model or vendor.
