Sequel

Integrations

How to connect Google BigQuery to AI agents?

Connect Google BigQuery to Sequel and query it in plain English — from the Sequel app or any AI tool wired up to the MCP server. BigQuery is Google's fully-managed, serverless data warehouse, and Sequel connects to it with a read-only Google sign-in so you can ask questions across your datasets without writing GoogleSQL by hand.

What you'll need

  • A Google Cloud project with the BigQuery API enabled.
  • A Google account with read access to the datasets you want to query — in practice the roles/bigquery.dataViewer role (to read tables) and roles/bigquery.jobUser role (to run queries).
  • Your GCP Project ID — the unique identifier for your project, e.g. my-company-analytics-123. You'll find it at the top of the Google Cloud Console, or by running gcloud config get-value project.

Connect with a least-privilege account

Sign in with an account that only has read access to the datasets you intend to expose. Sequel requests the read-only bigquery.readonly scope, so it can run SELECT queries but can never modify your data.

Connect it

Open a new connection

In the Sequel dashboard, go to Connections → New connection and choose BigQuery.

Sign in with Google

Authorize Sequel through Google OAuth 2.0. Sequel only requests the read-only bigquery.readonly scope — there are no service-account JSON keys to create or manage.

Enter your GCP Project ID

Provide the project you want to query.

GCP Project ID

my-company-analytics-123

Sequel verifies the project, confirms the BigQuery API is enabled, and checks that your account can list datasets.

Test and save

Sequel reads your datasets and table schemas. A green check means it's live. You can restrict schema introspection to specific datasets later from the connection settings.

Try it

Once connected, ask things like:

  • "What are the top 10 events by count this week?"
  • "Show me daily revenue for the past 30 days as a line chart."
  • "Which users had the highest session count last month?"
  • "List all tables in my analytics dataset with row counts."

Troubleshooting

SymptomLikely fix
"Access denied" / 403Make sure the BigQuery API is enabled and your account has bigquery.dataViewer (read) and bigquery.jobUser (run queries) roles.
"Project not found" / 404Double-check the GCP Project ID — use the project ID, not the project name or number.
Queries scan too many bytesBigQuery bills per bytes scanned. Add an instruction in the connection settings to always filter by partition columns on large tables.
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