Prepare for client calls with answers from your Airtable tables. Connect a base, select a table, and use ChatGPT or Claude through Catchr MCP to explore records, summarize selected columns, and check gaps before reporting.
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Each Airtable table has its own structure. Start by discovering its available columns, then choose the fields that matter for your client's report. Base, table, and record identifiers help you keep each answer tied to the right data.
Catchr discovers available Airtable data as Base / Table pairs. Select the pair you need and use Airtable Base Name, Airtable Table Name, and Airtable Record ID to identify the source of the records you review.
For agencies working across client bases, this makes the reporting scope explicit before analysis begins.
Discover the selected table's columns before choosing what to summarize. Use available numeric columns for totals, boolean columns for checks, and other selected columns to organize a report.
Linked records, attachments, and multi-select values are returned as JSON strings. Account for that format when requesting summaries; a linked-record value does not by itself provide the contents of the linked row.
Use Airtable Created Time to review records created within a chosen period. Include record identifiers so you can locate the rows behind the summary.
If your report needs a different date, discover the table's available date columns and select the appropriate one. Record creation time and a date stored in a column answer different reporting questions.
A focused table review, a recurring report, and a question through Catchr MCP serve different client needs. Choose the approach around the answer or deliverable you need from the selected Airtable records.
Use a focused analysis to investigate a table, assemble a report for repeatable client reviews, or use Catchr MCP to ask a specific follow-up question. In each case, select the Airtable columns and date scope that support the task.
Connect Airtable to Catchr with a personal access token that includes schema.bases:read and data.records:read, plus access to the bases you want to use. Select the discovered Base / Table pair, then connect your AI destination through Catchr MCP to start asking questions in ChatGPT or Claude.
Use these prompts to prepare a client review or check a table before reporting. Replace the bracketed values with your selections, and discover available columns before choosing fields for analysis.
Using Catchr, discover the available columns in [base / table]. Which columns can support a report about [client reporting question]? List their names and available types, explain relevant limitations, and ask me to select the columns before analyzing records.
Copy promptUsing Catchr, how many records in [base / table] have Airtable Created Time between [start date] and [end date]? Summarize the count by day and list the matching Airtable Record IDs with their creation timestamps. Use record creation time as the date basis.
Copy promptUsing Catchr, discover the columns in [base / table] and ask me to confirm [columns to check]. Which records have missing values in those columns? Report the missing-value count for each selected column and list the affected Airtable Record IDs, distinguishing missing values from zero or false.
Copy promptUsing Catchr, discover the numeric columns in [base / table] and ask me to select [numeric column]. Which records have a value above [threshold]? Show their Airtable Record IDs and selected values, sorted from highest to lowest, and calculate the total of that column across the matching records.
Copy promptUse an Airtable personal access token with schema.bases:read for discovering bases and tables, data.records:read for retrieving records, and access to your selected bases. Connect Airtable in Catchr, select a Base / Table pair, and connect ChatGPT or Claude through Catchr MCP.
Columns are discovered from the selected table, so there is no fixed list shared by every base. Ask for the available columns first, then select the ones to analyze. Airtable base, table, and record identifiers are also available to keep results traceable.
These complex values are returned as JSON strings. Account for that format in your reporting request, and do not assume that linked-record values include the contents of another table. Numeric, boolean, and date-like columns retain their native types in Looker Studio.
Yes. Airtable Created Time provides the creation timestamp for each record. Use it to review records created during a selected period. For a report based on another date, discover and choose the relevant date column from your table; creation time does not show when a record was last changed.
Connect your sources to Catchr, add the MCP server to your AI assistant, and ask about the work that matters now.
