Think inside your AI world.
Vercel + Linear through Unl
A deploy can be perfectly healthy and still be missing half of what the release promised. Ready means the build is clean and the scope is there — a gate across two tools.
Vercel + Linear through Unl reads the deployment’s health against the release scope committed in Linear, judged by the launch gate you set, so “ship this deploy?” returns a verdict with the unmet part named. The gate is held in Unl.
The criterion that binds them
Say you’ve ratified a launch gate: a clean Vercel deployment and the release’s committed Linear scope closed — because a healthy deploy that’s missing promised scope is a release only in name.
The two naked reads
Vercel returns the deployment status and logs. Linear returns the release’s scope and issue state. Both are right and partial; neither pairs deploy health to scope completeness, so “is this release actually done?” is yours to assemble.
The one measured answer
Against your gate: the deployment is clean, but three of the release’s committed items remain open in Linear — so the deploy is healthy and the release isn’t complete; ship it and you ship a promise half-kept.
And back again
If you lift an unfinished item out of the release, you settle that in Unl — and the following deploy read holds the gate to the scope you now expect.
The answer comes back measured against what you already decided, and why.
A router can place Vercel status beside Linear scope. It can’t rule the release complete-or-not, because the launch gate — deploy health and scope completeness together — lives in neither tool.
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.
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Questions people ask
Can AI tell me if a deploy is actually a complete release?
Yes, through Unl. You ratify a launch gate spanning a clean Vercel deployment and the closed Linear scope; the two are read together against it, so “ship this deploy?” returns a verdict with the unmet scope named.
Isn’t a healthy deploy a finished release?
A healthy deploy shows it built and ran; it says nothing about whether the promised scope is in it. The gate that joins deploy health to scope completeness lives in Unl, so the read won’t call a release done on green alone.
Does Unl change my Vercel or Linear state?
Unl reads through Vercel and Linear, 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
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.