Can I query Stripe in plain English instead of writing SQL?

Yes, once Stripe data is in BigQuery. Dataki has no Stripe connector of its own; it reads the dataset the data lands in (BigQuery's Stripe connector, in Preview), turns a plain-English question into SQL against it, runs it and returns a chart. The generated query is shown with every result, so you can verify or edit it.

How do I build a dashboard from Stripe data without an ETL pipeline?

Set up the route in the Stripe setup guide once. The copy into BigQuery then runs on its own, so there is no pipeline for you to maintain. Connect that dataset to Dataki, ask your question and keep the answer as a dashboard widget; Dataki queries the dataset at read time, so the dashboard is as fresh as the export.

Can Claude, ChatGPT or Cursor query my Stripe data?

Yes, through Dataki's hosted MCP server at https://dataki.ai/api/mcp. Connect Stripe to Dataki, add that URL as a connector in Claude or ChatGPT (or in Cursor, VS Code or Claude Code with a Dataki key), and the assistant can read the schema and run read-only queries. It gets the rows back; the credentials stay encrypted in Dataki and are never handed to the model.

Dataki for Stripe

Ask Stripe in plain English

Ask Stripe revenue questions in plain English. BigQuery's Stripe connector copies charges, customers, invoices and subscriptions into a dataset, and Dataki answers from it.

Through BigQuery BigQuery's Stripe connector, in Preview. The guide takes about 15 minutes.

Follow the setup guide Open Dataki

app.dataki.ai / chat BigQuery · stripe

What was our revenue each month this year, net of refunds?

Reading the schema, writing the query…

SELECT DATE_TRUNC(DATE(created), MONTH) AS month,
       SUM(amount) / 100 AS net_revenue
FROM   stripe.balance_transactions
WHERE  type IN ('charge', 'refund')
  AND  DATE(created) >= DATE_TRUNC(CURRENT_DATE(), YEAR)
GROUP BY month ORDER BY month

Net revenue grew every month this year, from $98k in January to $151k in September.

01Questions

What people ask Stripe

Each one becomes a query against the Stripe data, run read-only, with the SQL shown beside the chart so anyone who reads SQL can check it. Anything worth keeping goes on a dashboard that refreshes on its own.

What was our revenue each month this year, net of refunds?
How many subscriptions churned last month, and on which plans?
Which customers have failed invoices outstanding?
What is monthly recurring revenue by plan today?

02From your assistant

Ask Stripe from Claude, ChatGPT or Cursor

Dataki runs a hosted MCP server. Add it to your assistant once and it can read the Stripe data in BigQuery and run read-only queries through Dataki. The assistant gets the rows back; the credentials stay encrypted in Dataki and never reach the model.

Setup for your assistant:

Claude · dataki (MCP) BigQuery · stripe

From the Stripe data in BigQuery, chart monthly revenue net of refunds for this year.

list_sources · finds BigQuery · stripe
get_data_context · reads the tables and what the columns mean
query · runs the SQL read-only, returns the rows
render_ui · draws the chart from those rows, in the chat

server URL streamable http

https://dataki.ai/api/mcp

03Setting it up

Getting Stripe data to Dataki

BigQuery's Stripe connector, in Preview. The setup guide covers it step by step.

Setup: About 15 minutes.
Cost: Free while the connector is in Preview. BigQuery storage and queries are billed beyond the free tier.
Freshness: As often as you schedule it. Runs of one transfer cannot overlap, so leave room between them.
History: From a start date you choose. Left empty, three years back.

Read the Stripe guide Open Dataki

The answer is still there tomorrow.

Ask in plain language. Dataki writes the SQL, runs it against your warehouse and draws the chart. Anything worth keeping becomes a dashboard with a link — not a message that scrolls away.

app.dataki.ai / chat

Which channels actually brought in revenue last quarter?

Queried bigquery · payments · 1.2 GB scanned

SELECT channel,
       SUM(amount) AS revenue
FROM   payments
WHERE  created_at >= DATE_TRUNC(CURRENT_DATE(), QUARTER)
GROUP BY channel
ORDER BY revenue DESC

Revenue by channel

Q3 · 5 rows

Organic search: $412,900
Partner referral: $268,400
Email: $151,200
Paid social: $96,700
Direct: $61,300

One click later, that chart is a dashboard of its own:

app.dataki.ai/d/revenue-by-channel

Live, not a screenshot. It re-runs the query on a schedule, so the number your team reads on Friday is Friday's number.

Share the link with anyone. Viewers are free on every plan.
Edit the SQL by hand whenever the model gets the logic almost right.
Drop the same dashboard into your own product with one line of HTML.

Start free See how it works

Using Dataki with Stripe

Can I query Stripe in plain English instead of writing SQL?: Yes, once Stripe data is in BigQuery. Dataki has no Stripe connector of its own; it reads the dataset the data lands in (BigQuery's Stripe connector, in Preview), turns a plain-English question into SQL against it, runs it and returns a chart. The generated query is shown with every result, so you can verify or edit it.
How do I build a dashboard from Stripe data without an ETL pipeline?: Set up the route in the Stripe setup guide once. The copy into BigQuery then runs on its own, so there is no pipeline for you to maintain. Connect that dataset to Dataki, ask your question and keep the answer as a dashboard widget; Dataki queries the dataset at read time, so the dashboard is as fresh as the export.
Can Claude, ChatGPT or Cursor query my Stripe data?: Yes, through Dataki's hosted MCP server at https://dataki.ai/api/mcp. Connect Stripe to Dataki, add that URL as a connector in Claude or ChatGPT (or in Cursor, VS Code or Claude Code with a Dataki key), and the assistant can read the schema and run read-only queries. It gets the rows back; the credentials stay encrypted in Dataki and are never handed to the model.

Product

Solutions

Resources