Think inside your AI world.
How do I connect Jira to ChatGPT?
The Atlassian MCP surface — Jira issues, sprints, status, with Confluence alongside — answers ChatGPT the same way it answers every MCP client.
Direct answer: connect the Atlassian MCP surface to ChatGPT. In ChatGPT, add it from the connector settings (developer mode); the tool's own docs carry the current path. Authorise your site and ChatGPT reads Jira issues, sprints and status, plus Confluence docs — the ticket and the spec in one conversational reach.
Sprint state, asked plainly
What is mid-sprint and stuck, which stories have no estimate, what the epic's spec commits versus what its tickets deliver — cross-referenced live, from whichever assistant you have open when the question lands.
Carryover is a number you chose to care about
Worked case: your team ratified a carryover ceiling — no more than 15% of committed points roll to the next sprint, set after a quarter where chronic 30% carryover made every plan fiction. Jira computes carryover trivially; that 15% is where planning stops being honest is a standard you set about the computation.
Through Unl the sprint-close read arrives judged: carryover at 22% — past your ceiling for the second sprint, the fiction threshold. The retro starts from a breach of your own standard, which is a very different meeting from one that starts from a chart.
Jira to ChatGPT reads sprints and specs together; through Unl they are read against the planning standards you ratified — carryover becomes a verdict, not a shrug.
Reads through Unl arrive with measured context — in the presence of the decisions you’ve already settled. The reach lane is live: 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.
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Questions people ask
What does the Atlassian surface give ChatGPT?
Jira issues, sprints and status, and Confluence docs — the same paired read every MCP client gets.
Can I keep the connection read-only?
Scope what you authorise; conversational review needs reads only. Unl's own reads are one-way regardless — measured, never mutating.
Why ratify a carryover ceiling rather than just track it?
Tracking reports the number; ratifying makes the number answerable. The ceiling arrives inside every sprint read with its reason, so breaches confront instead of accumulate.
What if the carryover was deliberate?
Then record that it was, and the ceiling stops reading as a failure. A carryover rule that cannot tell a planned split from a slipped commitment will train you to hide the split. Say which it was at the time: the reason is the part worth having later.
What this is
Think inside your AI world — you stay in command
Save the thoughts, decisions and targets worth keeping, each with its reasoning, carried into every AI session the moment they matter. A new unit of exchange between you and your AI: the Settled Why with standing that travels. Unprompted.
Your whole AI world. What you decided at the epicentre. It plugs into Claude, Claude Code, ChatGPT and Cursor as an MCP connector — quick to connect, in a couple of steps.
MCP native·Human settled·Model agnostic·Your data
Measured Context
Connect Unl to bring the right information into the moment.
Your sources, read against the criteria you set.
The full product, open. Free at launch.