Chat with your Pagar.me data

AI to analyze Pagar.me data with Claude and ChatGPT

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No credit card required | 14 days | 10 million records | 30 pipelines

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Pagar.me
You
What was my total revenue from Charges yesterday?
Charges
Your Charges pipeline shows R$ 47.850 in approved transactions across 312 orders yesterday.
Via Kondado MCP
You
Which Customers segment has the highest average Order value?
Customers
Customers from São Paulo show an average Order value of R$ 342, 23% above your overall average.
Via Kondado MCP
You
How many Receivables are pending for next week?
Receivables
You have R$ 128.400 in Receivables scheduled to settle between March 15-21 across 89 transactions.
Via Kondado MCP
You
What is my current approval rate for card payments?
Charges
Your Charges data shows a 94.2% approval rate for card transactions this week, up from 91.5% last week.
Via Kondado MCP
Works in Claude, ChatGPT and any MCP client

AI to analyze Pagar.me data with Claude and ChatGPT

Ask Claude, ChatGPT or any MCP client about your Pagar.me payment data using simple natural language. Query your Charges pipeline to see daily sales volumes and success rates, check Orders status for fulfillment bottlenecks before they escalate, or compare Receivables trends against Balance Operations to understand cash flow timing. The AI reads your replicated financial data and returns instant answers about transaction metrics, customer payment behaviors, and revenue KPIs without manual spreadsheet exports or SQL queries.

Kondado replicates Pagar.me data through 8 pipelines to Claude, ChatGPT, and any MCP client, enabling natural language analysis of 344 fields covering Customers, Charges, Orders, Receivables, and Balance Operations. The same data also powers ready reports in Power BI and Looker Studio for visual recurring monitoring.

E-commerce managers ask about conversion rates by card brand directly in chat to optimize checkout flows, while finance teams query Receivables timelines to forecast working capital needs for the next quarter. Marketing analysts combine Customer segments with Orders data to calculate lifetime value by acquisition channel, and operations managers monitor Charges status to identify failed payment patterns requiring immediate attention. Every team accesses Pagar.me insights conversationally without technical setup, and can switch to ready reports when they need visual trend monitoring.

I prefer ready dashboards

Dashboard templates in Power BI and Looker Studio, connected to your Pagar.me data by Kondado in minutes.

View Pagar.me dashboards →

I want to ask the AI

Claude, ChatGPT and other MCP clients query your Pagar.me data in natural language.

View MCP setup →

The Pagar.me data source includes eight distinct pipelines that capture every aspect of your payment operations, from customer profiles to financial settlements. Query the Customers pipeline to segment buyers by location and contact history, analyze the Charges pipeline to identify peak sales hours and declined payment patterns, and review the Orders pipeline to track average ticket size and fulfillment status across your store. The Receivables and Balance Operations pipelines reveal cash flow timing and fee structures, while Customers: Cards and Customers: Addresses help you understand payment method preferences and geographic concentration. Combining these datasets in chat unlocks cross-analysis, such as correlating specific card brands with higher Order values or linking Customer segments to Receivables delays. Data updates on a configurable schedule, ensuring your AI answers reflect the latest transactions and balance movements.

How to connect Pagar.me to Claude, ChatGPT and other AI clients

MCP is an open standard. Add the Kondado server to the connections of Claude (Web or Desktop), ChatGPT, or any other MCP client you use, and authorize via OAuth at app.kondado.com.br. Setup through the UI, no code.

Kondado MCP server: https://mcp.kondado.io/mcp
Detailed guide: Claude Detailed guide: ChatGPT
AI vocabulary

Pagar.me tables and metrics available via Kondado

Each item below is something Claude, ChatGPT or another MCP client already knows how to query — no schema setup, no manual mapping.

8
Tables
344
Fields
∞
Ad-hoc questions
Customers
Includes information such as customer name, email, and status, along with address and phone data like area code and number.
Customers: Cards
Records card details including brand, expiration date, and status, along with cardholder name and card digits.
Customers: Addresses
Contains address data such as city, state, and country, along with creation date and address status.
Charges
Includes information on charges made, such as amount, date, and status, along with details of the associated customer.
Balance Operations
Records operations related to balance, including operation type, amount, and transaction date.
Orders
Contains details of orders placed, such as total amount, status, and creation date, along with customer information.
Recipients
Includes information about recipients, such as name, document, and status, along with creation and update data.
Receivables
Contains information about receivables, including amount, due date, and status, along with details of the associated customer.
Full docs on the wiki → Connect Pagar.me now →

How to connect and use AI with your data

In 3 steps: connect on Kondado, pick dashboard or chat, analyze.

1
Connect Pagar.me at app.kondado.com.br

Log in to Kondado and select Pagar.me as your data source, then choose a 'Via Kondado destination' so your payment data lands ready for AI access and report templates.

2
Add Kondado MCP in Claude or ChatGPT

Open the connection settings in Claude Web or Desktop, or in ChatGPT, add the Kondado MCP server, and authorize once via OAuth. Other MCP clients also work with this same GUI-based configuration.

3
Ask about Pagar.me data in chat

Start asking natural language questions about your Charges, Orders, and Receivables. For visual recurring monitoring, open a ready Power BI or Looker Studio report template.

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Same Kondado data, in chat through Claude, ChatGPT and other MCP clients.

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Related on Kondado

Frequently asked questions about AI

How ready dashboards and chat via Claude / ChatGPT work together with your data via Kondado.

What specific business questions can Claude or ChatGPT answer about my Pagar.me sales and payments? ▼
Claude and ChatGPT can answer questions about daily sales volumes from the Charges pipeline, approval rates by card brand, customer segmentation using the Customers and Customers: Cards data, and cash flow forecasting based on Receivables due dates. You can ask for specific comparisons like "Which state has the highest average Order value?" or trend analysis across your Balance Operations.
How do I configure Claude Web or Desktop to access my Pagar.me data through Kondado? ▼
In Claude Web or Desktop, navigate to the connection settings and add the Kondado MCP server. Authorize once via OAuth at app.kondado.com.br to grant access to your Pagar.me pipelines. Other MCP clients also work with this same GUI-based setup, requiring no command line tools or code.
How does authentication work when connecting ChatGPT to Pagar.me via Kondado? ▼
Authentication uses OAuth 2.0 through app.kondado.com.br. When you add the Kondado MCP server in ChatGPT, you will be redirected to sign in and authorize data access.
Can the AI execute actions on my Pagar.me account or only read data for analysis? ▼
The AI provides read-only analytical chat. It can query your replicated Charges, Orders, Customers, and Receivables data to generate insights, but cannot initiate refunds, create transactions, or modify any data in your Pagar.me account. All interactions are limited to data analysis and reporting.
How often is my Pagar.me data updated for AI analysis? ▼
Pagar.me data replicates on a configurable schedule that you set in Kondado, ranging from near-real-time intervals to daily updates. This ensures your AI conversations reflect recent transactions, keeping your cash flow and sales analyses current without claiming instantaneous synchronization.
What report templates are available for visual monitoring of Pagar.me metrics? ▼
Kondado offers ready report templates in Power BI and Looker Studio that visualize Pagar.me metrics like revenue trends, payment method breakdowns, and receivables aging. These templates use the same replicated data as the AI chat, providing visual reports for recurring monitoring.
What is the difference between asking the AI in chat and opening a ready report? ▼
AI chat offers exploratory analysis where you ask spontaneous questions about specific Charges, Customer segments, or Balance Operations in natural language. Ready reports provide fixed visual dashboards for routine KPI monitoring. Use chat for deep-dive investigations and reports for standardized visual tracking.

Try out all the features for free for 14 days