Confluence integration

Confluence in Polar: your numbers, written into Confluence.

Confluence is where your team works. Connect it and an agent reads your governed metrics over the Polar MCP, then writes to your docs, summaries and reports, on a schedule and sourced to the data. Polar is the numbers; Confluence is where they live.

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Get Polar in Confluence See the setup
Google Sheets → Polar

What you can bring in

Daily exec summary
"Write today's summary?"
Sales, new and repeat customers, drafted into your doc every morning.
daily summary
Metric write-up
"Explain why CAC moved, in the doc."
A short, sourced narrative next to the number, not just a figure.
the number + the why
Board / investor page
"Draft the monthly update."
Actuals vs plan and the top flags, assembled before the 1st.
actuals vs plan
Sourced, not guessed
"Are the numbers right?"
Every value comes from Polar's governed metrics, first-party and sourced.
first-party, sourced
On a schedule
"Do I have to ask each time?"
Set it once; it writes to Confluence on a cadence, no prompt needed.
cron · no prompt
Two connectors
"Does an AI reason on it?"
The Polar MCP and Confluence together, sourced to each.
two connectors

Confluence is where you work. Polar puts the numbers in it.

Confluence is where your team plans and executes, but the numbers live in a dashboard nobody opens. Connect an agent to both and Polar's governed metrics write themselves into Confluence, where the work actually happens.

Confluence on its own

  • Numbers copied in by hand from a dashboard.
  • Stale figures that drift the moment they're pasted.
  • No link between the work and the data.
  • Reporting is a manual chore.

Confluence with Polar

  • Governed metrics written in automatically, sourced.
  • Refreshed on a schedule, always current.
  • The data lives where the work happens.
  • Summaries and reports write themselves.
Setup Guide

Write Polar's numbers into Confluence.

01 · What you need
Polar

A Polar account with Shopify

A Polar account with Shopify connected. This connector plugs in right next to your stack.

Connect your data →

A Confluence workspace

A Confluence workspace and the place summaries and reports will land, plus Confluence connected for the agent.

Open Confluence →

An agent with both

An assistant with the Polar MCP and Confluence, so it reads your data and writes to Confluence in one flow.

02 · Connect Polar and Confluence to your agent
1

Give your agent the Polar MCP ~2 min

Governed metrics, sourced.
Connect the Polar MCP to your assistant so it reads your governed semantic layer, first-party and sourced.
2

Connect your Confluence ~2 min

Where it writes.
Point the agent at Confluence. It uses two connectors together: Polar for the numbers, Confluence to write them where your team works.
3

Write and schedule the payoff

On a cadence.
Ask once and it writes to your docs. Set it on a schedule and it writes summaries and reports to Confluence every morning, before anyone opens it.
Get started

Put your numbers where your team already works.

Give an agent the Polar MCP and your Confluence, and let it write summaries and reports, on a cadence, sourced to your data.

Book a demo Connect your data ↗
The Gap

The connector is only half of it.

Once the summaries are connected to Polar, you can use them wherever you already work. Ask Polar in plain language, pull them live through the Polar MCP, or schedule a snapshot into the report your team reads every morning.

Confluence

the numbers to write
Polar

Polar

summaries and reports

Ask Polar

Polar MCP

Scheduled reports

Featured Use Case

Your numbers, where the work is.

Your numbers, where the work is

Your team plans and executes in Confluence, not in a dashboard, so the numbers that should drive the work sit somewhere else and go stale. Ask once for a daily summary or a monthly update and it reads your governed metrics and writes them into your docs, on a schedule, sourced to the data. Because it runs on the Polar MCP, every figure is governed and sourced, and because it runs on a schedule, it is there before anyone asks.

What makes it real

Written for you. An agent reads Polar and writes summaries and reports into Confluence, sourced.

On a schedule. Set once; it writes on a cadence, no prompt needed.

Ask Polar, in plain language. “Write today's numbers into Confluence.” No SQL, no export.

See how it writes to Confluence
Other Use Cases

Other use cases

Use case 01

Placeholder

Placeholder. The use case skill fills this. (rung: see it)

See the use case › Use case 02

Placeholder

Placeholder. The use case skill fills this. (rung: report it)

See the use case › Use case 03

Placeholder

Placeholder. The use case skill fills this. (rung: analyze it)

See the use case › Use case 04

Placeholder

Placeholder. The use case skill fills this. (rung: decide from it)

See the use case › Use case 05

Placeholder

Placeholder. The use case skill fills this. (rung: act on it)

See the use case ›
Your Prompt Library

Confluence in plain language

A scannable wall of sample prompts for your Confluence data inside Polar. Ask Polar, or Claude with the Polar MCP connected.
See it
Write today's key numbers into Confluence.
Push summaries and reports to Confluence.
Show what the agent can write.
Analyze it
Draft a metric write-up in Confluence explaining the biggest mover.
Write last week's summary into Confluence.
Update Confluence with yesterday's numbers.
Decide from it
Turn this week's performance into summaries and reports in Confluence.
Schedule a weekly write to Confluence.
Route the numbers to the right place in Confluence.
Get started · connect once · written to Confluence

Your numbers, written into Confluence.

Connect Polar and Confluence to one agent, and let summaries and reports land in your workspace, blended and sourced to the data.

Get started by booking a demo Connect your data in Polar
Phase 1 ~5 minConnect your data in PolarPolar's semantic layer turns your stack into governed metrics.
Phase 2 ~2 minGive an agent Polar + ConfluenceConnect the Polar MCP and your Confluence to the same assistant.
Phase 3 the payoffWrite and scheduleSummaries and reports write themselves to Confluence on a cadence.