From connected to activated: onboarding for PandaDoc MCP connector

Company

PandaDoc

Year

2026

Area of focus

Growth

AI & Conversational UX

Prototyping

PandaDoc’s MCP connector lets AI assistants such as Claude and ChatGPT read, create and send documents on a user’s behalf. Plenty of people connected it. Too few of them ever used it.



My role. The PM gave me the goal and left the approach open, as long as it was technically feasible. I owned problem framing, the design direction, UX and UI, and I monitored the experiment.
An engineering spike ran alongside to test what the platforms would allow. Engineering owned the build. The OAuth code belongs to the Signup team, and the MCP team and Legal reviewed the content.

PandaDoc’s MCP connector lets AI assistants such as Claude and ChatGPT read, create and send documents on a user’s behalf. Plenty of people connected it. Too few of them ever used it.

My role. The PM gave me the goal and left the approach open, as long as it was technically feasible. I owned problem framing, the design direction, UX and UI, and I monitored the experiment. An engineering spike ran alongside to test what the platforms would allow. Engineering owned the build. The OAuth code belongs to the Signup team, and the MCP team and Legal reviewed the content.

The Problem

The Problem

35% of accounts that connected the MCP made no calls to it at all: nothing read, written or removed. The connection worked, but nobody took the next step.


At first it looked like a consent problem. The flow showed two dense screens: an access request, then an OAuth screen that repeated the same long permission list. Before anyone saw a reason to connect, the AI client warned that “apps may introduce elevated risk”.

35% of accounts that connected the MCP made no calls to it at all: nothing read, written or removed. The connection worked, but nobody took the next step.

At first it looked like a consent problem. The flow showed two dense screens: an access request, then an OAuth screen that repeated the same long permission list. Before anyone saw a reason to connect, the AI client warned that “apps may introduce elevated risk”.

Current flow. The first of two dense screens asks the user to trust a callback address before they’ve seen any reason to connect.
The second screen lists permissions, with an account and a workspace selector that offers no real choice.
On the third screen the connection succeeds and sends the user back to the AI client.

Current flow. The first of two dense screens asks the user to trust a callback address before they’ve seen any reason to connect. The second screen lists permissions, with an account and a workspace selector that offers no real choice. On the third screen the connection succeeds and sends the user back to the AI client.

Current flow. The first of two dense screens asks the user to trust a callback address before they’ve seen any reason to connect. The second screen lists permissions, with an account and a workspace selector that offers no real choice.
On the third screen the connection succeeds and sends the user back to the AI client.

Decision log

Treat the gap between connecting
and first use as the real drop-off

Treat the gap between connecting and first use as the real drop-off

Treat the gap between connecting
and first use as the real drop-off

But in review we established that the drop-off happens after the connection succeeds: connected, then no first use.

2 / 2 · back

Context. The obvious target was the consent screen, because it was dense and had a lot of friction.

1 / 2 · read on

Options. Polish the consent screens, or design a bridge from “connected” to a first useful action.

Trade-off. A cleaner consent screen would help trust but could not move a metric that is lost later in the flow.

Decision. Keep the consent work small and spend the effort on the moment after connection.

Design for how the metric is defined

Design for how the metric
is defined

Design for how the metric is defined

The assistant can answer that from its own knowledge without calling a single PandaDoc tool, so the prompt could look helpful and still leave activation at zero.

2 / 2 · back

Context. Activation is defined as the first successful API request. The first idea was a starter prompt: “Show me what is possible with PandaDoc.”

1 / 2 · read on

Options. A capability tour, a general discovery prompt, or a task prompt that needs the user’s own data.

Trade-off. A task prompt shows one capability rather than all of them.

It forces a real read call, returns the user’s own documents, and points straight at the next action: chasing a signature.

2 / 2 · back

Decision. “@PandaDoc, show me my recent documents and which ones are still waiting on a signature.”

1 / 2 · read on

Merge two screens into one

Merge two screens into one

Context. The engineering spike showed that the access-request screen and the OAuth screen were technically the same step, shown twice.

Options. Keep two screens and give each one job, or merge them.

Trade-off. One screen has to carry identity, workspace, permissions and legal text without becoming a wall of text.

Decision. One screen, in a fixed order: who you are, where access applies, what the assistant can do, then the legal line and Connect.

Design direction. One consent screen now covers who you are, where access applies and what the assistant can do.
Instead of ending on a success screen, the next step hands over a ready task prompt that can only be answered
from the user’s own PandaDoc data, and Continue unlocks only once it’s copied.
The user returns to the AI client with a real first request in hand, so activation happens in the chat, not on our screen.

Design direction. One consent screen now covers who you are, where access applies and what the assistant can do. Instead of ending on a success screen, the next step hands over a ready task prompt that can only be answered from the user’s own PandaDoc data, and Continue unlocks only once it’s copied. The user returns to the AI client with a real first request in hand, so activation happens in the chat, not on our screen.

Write permissions as consequences,
not API scopes

Write permissions as consequences, not API scopes

Write permissions as consequences,
not API scopes

Context. Users saw six bundled capabilities in system language and had to accept them all or nothing.

Read is required and says “Nothing will be created or changed”. The other two are labelled clearly, and payment actions sit under Send and publish. A user can see the risk of each group before deciding.

2 / 2 · back

Decision. Three groups based on what changes in the account: Read your content, Create and edit content, and Send and publish documents.

1 / 2 · read on

Remove choices the user can’t actually make

Remove choices the user can’t actually make

Context. Through regular syncs with engineers I tested every element. The workspace was shown as a selector, but in this flow there was nothing to choose.

A control that does nothing makes people doubt the rest of the screen.

2 / 2 · back

Decision. Show the workspace as fixed context next to the account, with one line of explanation: “Access is scoped to your role and workspace permissions.”

1 / 2 · read on

Work within the legal and platform constraints

Work within the legal and platform constraints

Legal. Legal required the consent text to sit below the Connect button. I kept that and gave it a clear type hierarchy so it reads as part of the decision, not small print.

ChatGPT. ChatGPT already shows a suggested prompt in its empty state after a connector is installed. Rather than add a screen of our own, we put our prompt there. Using the platform’s own pattern cost less than inventing one.

Outcome

Outcome

+5pp

+5pp

activation, top of the 3–5pp target

activation, top of the 3–5pp target

70.5%

70.5%

activation rate, up from 65.5%

activation rate, up from 65.5%

1,000

1,000

accounts in the A/B test

accounts in the A/B test

accounts in the A/B test

2 weeks

2 weeks

live experiment, SMB and mid-market

live experiment, SMB and mid-market

live experiment, SMB and mid-market

Reflection

Outcomes

Outcome

What I’d take forward

A metric’s definition is a design input

The most useful change here wasn’t visual. It was noticing that a friendly prompt could avoid the event we were measuring.

Small engineering spikes settle design debates

Merging the two screens came from a technical finding, not from arguing over a mock-up.

Next question: graduated consent

Starting with read-only access and asking for write access when it’s first needed might lower the risk at the very first moment. I’d test it next.

Open to challenges
and opportunities

© 2026 Adelina Mokliak

Open to challenges
and opportunities

© 2026 Adelina Mokliak