Think inside your AI world.

Typeform through Unl

A finished Typeform proves someone filled in the boxes. Whether they're a lead worth chasing is a different question, and it needs its own rule.

Typeform through Unl reads form and response data against the lead-qualification rule you have ratified, so 'is this respondent a qualified lead?' comes back not yet qualified with the condition it hasn't met.

What Typeform holds

Typeform through Unl can genuinely read:

  • Individual form details and the full list of forms owned by an account.
  • Row-level response data for any field, through the insights tools built for exactly that.
  • The schema of analytics data available on a form, so a query knows what it's asking for.
  • Contacts and their properties, including how a form's answers map onto them.
  • Workspaces and accounts a given user can actually see.

What the naked read gives you

Typeform will tell you, precisely, that a new submission on the demo-request form answered '50-200 employees' and 'this quarter': real, structured response data, captured exactly as the respondent gave it, with nothing lost in translation.

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

What changes when Typeform is read measured

RevOps ratified that a response only counts as a qualified lead once company size is above 50 employees and the stated timeline is within two quarters, because smaller or vaguer submissions convert at a fraction of the rate and shouldn't queue-jump the sales team.

'Is this respondent a qualified lead?' returns, measured: not yet qualified - company size clears the bar but the stated timeline is 'just researching', short of the two-quarter window in the ratified rule. Typeform supplied the response data; your ratified rule supplied the qualification criteria.

And back again

Whoever picks up the lead next, whether that's sales, marketing or an SDR triaging the inbox, sees the same call, built from the same rule, rather than re-reading the raw answers and forming a fresh opinion each time.

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

Does the qualification verdict change if the respondent replies again?

It can. Unl re-reads Typeform's response data each time the question is asked, so a follow-up answer that moves the stated timeline inside two quarters flips the same lead to qualified on the next check.

How do I connect Typeform to Claude?

Add Typeform's own MCP server as a source in Unl and authorise it against the Typeform account whose forms and responses you want it to read. Access follows whatever that account is already permitted to see.

Can Unl edit or send a Typeform form through this connection?

No. The connection is read-only from Unl's side: it pulls form, response and contact data to check against your ratified qualification rule, and has no path to create, publish or alter a form.

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.