Prepare data before every question.
- Export files from the marketing platform
- Reformat and reconcile columns
- Rebuild the analysis for each follow-up
Three steps to your first source-aware prompt.
Meta Ads
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Configure the Catchr remote MCP connection in Claude using the connector details from Catchr.
Replace account, period, KPI target, and threshold variables before you ask Claude.
“Why did CPA rise?” sounds simple. The answer is usually buried across exports, formulas, filters, and tabs before the analysis can even start.
Choose the right account, date range, breakdowns, and fields. Then wait for the file and do it again when the question changes.
Rename columns, fix formats, join tabs, and check formulas before you can trust the comparison.
Turn the numbers into a client-ready answer, then repeat the whole process for the inevitable follow-up.
Catchr MCP gives Claude access to the marketing accounts you select, so each follow-up starts with the same marketing context instead of a new manual export.
Choose your role, open a workflow, then replace the bracketed variables before pasting the prompt into Claude. Every prompt asks for evidence, limits, and a concrete output.
Clear answers for marketers comparing connectors, data sources, reporting workflows, and dashboard setup.
Claude can analyze records from an Airtable base and table selected through Catchr. Available fields are discovered from that table, so the analysis can reflect its text, numeric, boolean, date-like, linked-record, attachment, and multi-select data when those fields are present and permitted.
Catchr discovers Airtable sources as Base / Table pairs. Select the relevant pair so Claude works with records and fields from the intended table rather than mixing unrelated datasets.
Yes, when the selected table contains suitable date-like data. Claude can use supported date breakdowns such as day, week, month, quarter, year, and hour to summarize or compare records over time.
Catchr preserves linked records, attachments, multi-select values, and other complex Airtable data as JSON strings. Claude can inspect these values, while numeric, boolean, and date-like scalar fields retain native types for clearer analysis.
Catchr maps dynamically discovered fields with Airtable field IDs rather than display names, helping the mapping remain stable when a field is renamed. Use clear current field names in your prompt so Claude can present the result understandably.
Yes, provided each Base / Table pair is available through Catchr. Ask Claude to review each dataset separately first, then compare only fields whose meanings, types, dates, and identifiers are compatible.
Yes, when the other sources are also connected through Catchr. Give Claude the shared dates, identifiers, and business definitions, and request a side-by-side analysis when the datasets do not support a reliable join.
You need an Airtable personal access token with access to the relevant bases and tables, an Airtable source connected in your Catchr workspace, and Catchr MCP enabled in Claude. The records and fields Claude can use depend on the token's permissions and the selected Base / Table pair.
Claude analyzes the Airtable records returned through the Catchr connection and should not assume they are real time. Ask Claude to identify the latest available date-like value, the requested period, and any missing intervals before drawing time-based conclusions.
No. Catchr MCP provides Airtable data to Claude for analysis and does not grant write access to edit fields, add records, remove attachments, or change bases and tables. Make any operational changes directly in Airtable with the appropriate permissions and review.
Our team is always here to answer any questions you may have about our data connector.
Connect your marketing platform to Claude with Catchr MCP and start investigating current campaign performance.