Airtable AI — Automate Airtable with Runner

Ask for the records you need, and let Runner keep the base up to date.

Runner connects to Airtable through its first-party MCP server with schema-first queries, record search, and batch writes for reliable data operations.

What Runner does in Airtable

Example asks

Query filtered records

Pull all records from the pipeline tracker where status is 'Active' and close date is this quarter.

Runner queries the base with the right formula instead of pulling everything and filtering manually.

Inspect the schema before writing

Show me the field names and types in the customer feedback base before I add records.

Writes land in the right fields instead of being silently dropped.

Batch update records

Update the status to 'Complete' for the three tasks I just finished.

Multiple records update in one pass without manual base editing.

Create records from workflow output

Add a new row to the customer feedback base with the sentiment, source, and summary.

Structured workflow outputs land directly in the operating base.

Browse all Runner apps and integrations