Prepare your next client call with a clearer view of Pipedrive leads and contact activity. Connect Pipedrive to Catchr, choose ChatGPT through Catchr MCP, and ask questions about the columns available in your account.
For freelancers and agencies, that means turning CRM reporting questions into focused reviews of lead sources, expected close dates and outstanding activities.
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Start by discovering the available Pipedrive entities and columns, then select what your client report needs. Pipedrive uses a live schema, so confirm the available fields before building a query.
Use lead titles, IDs, source names, owner IDs and archived status to organize a lead review. Lead amounts and currencies add context when discussing the opportunities recorded in a client's CRM.
Compare lead counts by source or owner, and keep amount totals separate by currency. Treat lead amounts as recorded lead values, not realized revenue.
Lead added dates, updated dates and expected close dates answer different questions: when leads entered the CRM, which records changed, and which leads have an expected close date in your review period.
Deal added dates support a separate review of newly added deals. Select the date column explicitly so a report about expected closes does not become a report about record creation.
Person-level counts cover activities, done activities, undone activities, email messages and open, closed, won or lost deals. Select available person columns to identify the records you want to review.
Use these counts to surface contacts with outstanding activities or open deals before a client meeting. Keep direct, related and participant deal counts separate rather than adding them into a potentially overlapping total.
A focused lead review, a recurring client report and a follow-up question each need a different approach. Choose the method that fits the question and where you want to use the answer.
Use a report to give clients a consistent view of their Pipedrive data. Use Catchr MCP when you need to explore a specific question, such as which lead sources account for the most leads or which contacts have outstanding activities.
Connect Pipedrive to Catchr using OAuth and select the relevant client account. Choose ChatGPT or Claude through Catchr MCP as your AI destination.
Before your first analysis, ask for the available Pipedrive entities and columns. Select the fields you need, then specify your account, filters and date basis. Reporting queries do not modify Pipedrive source data.
Replace the bracketed values with your client's account and reporting choices. Each prompt starts with field discovery so the analysis uses columns available in the connected account.
Using Catchr, which lead sources brought in the most leads for [account] between [start date] and [end date]? Discover the available lead columns and confirm lead ID, added date, source name, amount and currency before querying. Use my selected columns [lead columns], filter by lead added date, and count distinct lead IDs by source. If amount and currency are selected, summarize amounts separately by currency. Show missing source names as a separate group.
Copy promptUsing Catchr, which non-archived leads in [account] have an expected close date between [start date] and [end date]? Discover the available lead columns, then use my selected columns [lead columns] to show lead ID, title, owner ID, expected close date, amount and currency where available. Sort by expected close date and summarize the lead count by owner ID. Describe these as expected closes, not confirmed sales.
Copy promptUsing Catchr, which person records in [account] have at least [minimum open deals] open deals and at least [minimum undone activities] undone activities? Discover the available person columns and use my selected identifying columns [person columns]. Return the matching records with open deal, done activity and undone activity counts, sorted by undone activity count. Keep direct deal counts separate from related and participant counts, and do not infer activity due dates from these totals.
Copy promptUsing Catchr, which non-archived leads in [account] were added between [start date] and [end date] and last updated before [cutoff date]? Discover the available lead columns and use my selected columns [lead columns], including lead ID, title, added date, updated date, owner ID and source name where available. List matching leads from oldest update to newest and summarize counts by owner ID. Report missing update dates separately and treat the results as records to review, not proof that no follow-up occurred.
Copy promptConnect your Pipedrive account to Catchr using OAuth, select the relevant account, and choose ChatGPT through Catchr MCP. Start by discovering available entities and columns, then select the fields for your first lead or contact activity question.
Use lead added dates for incoming leads, updated dates for record changes, and expected close dates for a forward-looking review. Deal added dates describe when deals were added. An expected close date does not confirm a sale.
You can review lead amounts alongside their currencies. Keep totals grouped by currency; a combined total needs an agreed currency conversion method. Lead amounts describe recorded lead value and should not be presented as realized revenue.
Review the available lead and person columns first. Leads include a person ID, but combining datasets requires a compatible identifier in the selected person columns and a verified matching approach. Do not assume an automatic join; separate lead and contact summaries can still support a client review.
Connect your sources to Catchr, add the MCP server to your AI assistant, and ask about the work that matters now.
