Build context through normal work
Plan actions, write inside them, and tag the material worth keeping. The workspace becomes useful context without a separate AI-preparation process.
AI agent workspace
Give AI the work behind the prompt.
Connect a compatible remote MCP client so an agent can find actions, read the notes behind them, and—when write access is granted—help move the work forward.
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The challenge
A good prompt cannot replace missing history.
AI is most useful when it can see the goal, current plan, source material, earlier decisions, and the state of the work. Copying that context into every conversation is slow, incomplete, and quickly out of date.
Connect with explicit permission
Add the ActionDrivenNote remote MCP endpoint to a compatible client, sign in, and review whether the client is requesting read or write access.
Let the agent retrieve what matters
Ask the client to list or search actions, inspect status and due dates, follow action structure, and read the selected action document as Markdown.
Write results back when appropriate
With write access approved, a compatible agent can create or update actions, edit documents, manage tags, and attach files through the available tools.
Context
Less copying between tools
The agent can retrieve current workspace context instead of relying on a pasted snapshot.
Control
Permission remains explicit
Authentication and requested scopes make the boundary visible before the client receives access.
Continuity
Useful output can remain
Approved results can return to the action, be tagged, and become part of the context available next time.
Related article
Why starting with action creates better working context
Understand the Plan → Think → Keep workflow that gives both people and connected agents a more meaningful workspace.
Read the article →