Think inside your AI world.

Jira through Unl

Jira shows the sprint board precisely. Whether the sprint is being run to the rule you set is your judgement — and scope creep looks normal from inside the board.

Jira through Unl reads your live project — issues, sprints, status, docs — against the sprint-commitment rule you have ratified, so drift comes back flagged with the rule it breaks.

What Jira holds

Jira’s MCP surface exposes the delivery surface (with Confluence docs):

  • Issues and their status
  • Sprints
  • Confluence docs and sprint context

What the naked read gives you

A naked read returns the sprint’s issues and burndown. Accurate, and it won’t flag that three issues were added after the sprint started, because “no scope added mid-sprint” is your rule, not a Jira control it enforces.

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

What changes when Jira is read measured

Say you've ratified a sprint-commitment rule: no scope added after day one, and carry-over kept under 20% — rules you set to keep estimates meaningful.

“Is the sprint being run to plan?” returns, measured: no — three issues were added on day four, breaching your no-mid-sprint-scope rule, and projected carry-over is 28%, over your 20% limit. Both are the rules you set to keep the sprint honest. Jira supplied the board; your ratified rule supplied the checks and the reasons.

And back again

If you allow a hotfix as a sanctioned mid-sprint addition and record it, the next read counts it as an allowed exception rather than a breach.

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 AI check a Jira sprint against our rules?

Yes, through Unl. You ratify the sprint-commitment rules (no mid-sprint scope, a carry-over limit, with reasons), and the live sprint is measured against them — drift is flagged with the rule it breaks.

How do I connect Jira to Claude?

Jira offers an MCP server over issues, sprints and Confluence docs. Through Unl the same board arrives measured against your ratified rules, so the sprint reads as on-rule or drifting.

Does Unl change my Jira issues?

Unl reads through Jira, and can write back on your explicit gesture — it never acts as a side effect of a read.

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.