Think inside your AI world.

Trello through Unl

Trello shows the card and the list it's sitting in. Whether the work behind that card is actually finished is your call - a card in Done isn't proof the checklist is.

Trello through Unl reads boards, cards and checklists against the finished criterion you have ratified, so 'is this card actually done' comes back ready-or-flag with the condition it hasn't met.

What Trello holds

Trello's official MCP server exposes:

  • search for cards and boards by keyword
  • board, list and card retrieval, including card content and position
  • checklist retrieval on a card
  • member and workspace inspection

What the naked read gives you

Ask Trello's own MCP where the launch-asset card sits and it tells you: Done list, moved there this morning, assigned to the designer. That's an accurate read of the board's current shape. What it doesn't say is whether the three-item checklist on that card - final copy approved, alt text added, file exported - actually got ticked off before the card moved, or whether someone just dragged it across to clear their view. Trello knows exactly which list holds the card; deciding what finished requires isn't something a list position can settle.

The frame judges the data it is given; it does not verify the source’s accuracy.

What changes when Trello is read measured

Your campaign lead ratified the rule in Unl: a card only counts as done once it's in the Done list and every item on its checklist is ticked - because a card dragged over with an open checklist is still unfinished work wearing a finished label.

'Is the launch-asset card actually done' returns, measured: not met - the card is in Done, but the checklist shows 'alt text added' still unticked. Trello supplied the card's list position and checklist state; your ratified rule supplied the finished criterion.

And back again

The judgement is ratified and held in Unl, so 'done' for this board keeps its checklist meaning and the next card dragged into Done is tested against it, not trusted for the column it happens to sit in.

The answer comes back measured against what you already decided, and why.

The lane is live and open to this tool today: one box, paste anything. If it speaks MCP, Unl can reach it. Readings arrive unprompted, the data beside the criterion; Unl is a courier, not a warehouse, and keeps only your keys and the frame.

Questions people ask

Can Trello tell me if a card is actually finished?

Trello's MCP returns the card's list position and its checklist state; it doesn't decide what finished means. That's the criterion you ratified in Unl, which turns the card read into a verdict.

How do I connect Trello to Claude?

Trello runs its own official hosted MCP server at mcp.trello.com - you authorise it via an OAuth consent screen when you connect Claude or another compatible AI assistant, with no API token to manage.

Does connecting Trello let Unl move my cards?

No - Unl reads the boards, cards and checklists Trello's MCP exposes. It doesn't drag cards or tick checklist items on your behalf.

What this is

Think inside your AI world — you stay in command

Unlimitless (Unl to friends) holds what you've settled, reads what your tools are showing, and catches what's changed out in the world — and hands your AI whatever bears on the work, the moment it's needed, without you asking. The right thing, in front of the model, unprompted, with you in command of the call. So you keep moving toward what you set out to build, on top of everything you've already decided.

It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector. Quick to connect, in a couple of steps.

Unlimitless is open now to invited Alpha. Apply for the Beta waitlist to come in ahead of the full launch:

Alpha is invite-only · free at launch.