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Hotmart is a digital platform that enables creators to sell digital products and online courses. It provides a comprehensive ecosystem for digital product creators, including tools for hosting, payment processing, and managing student access.

Configuring Hotmart as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the Hotmart option from the list of connectors. Click Next and you’ll be prompted to add your access.

1. Add account access

You’ll need your Hotmart API credentials for this connection. You can obtain these from the Hotmart Developer Portal (check official docs). Once you have them, add the following credentials:
  • Client ID: The client ID to authenticate against the API service.
  • Client secret: The client secret to authenticate against the API service.
  • Token: The basic token to authenticate against the API service. You should pass only the token value without the Basic prefix.
  • Members area subdomain: The subdomain of your member’s area. It can be extracted from your hotmart.com/club/{subdomain}. The Students stream is only available when this field is filled in.
  • Start date: Records created or updated after the start date will be extracted from the source.
Under Advanced settings you can also tune how the connector slices date-filtered requests. Each option defaults to 365 days and only needs to be reduced (e.g. 30 or 15) if you keep hitting timeout errors on the corresponding streams:
  • Sales window (days): Number of days per request window for the Sales History, Sales Commission and Sales Participants streams.
  • Price details window (days): Number of days per request window for the Price Details stream.
  • Subscription window (days): Number of days per request window for the Subscriptions and Subscription Transactions streams.
Once you’re done, click Next.

2. Select streams

Choose which data streams you want to sync - you can select all streams or pick specific ones that matter most to you. The available streams include sales history, subscriptions, products, and more.
Tip: The stream can be found more easily by typing its name.
Select the streams and click Next.

3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table (which will effectively contain the fetched data) and the type of sync.
  • Layer: choose between the existing layers on your catalog. This is where you will find your new extracted tables as the extraction runs successfully.
  • Folder: a folder can be created inside the selected layer to group all tables being created from this new data source.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix to all tables at once and make this process faster!
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every time the extraction happens, we’ll get only the new data - which is good if, for example, you want to keep every record ever fetched.
    • Full table: every time the extraction happens, we’ll get the current state of the data - which is good if, for example, you don’t want to have deleted data in your catalog.
Once you are done configuring, click Next.

4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. This decision usually depends on how frequently you need the new table data updated (every day, once a week, or only at specific times). Optionally, you can define some additional settings:
  • Configure Delta Log Retention and determine for how long we should store old states of this table as it gets updated. Read more about this resource here.
  • Determine when to execute an Additional Full Sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while.
Once you are ready, click Next to finalize the setup.

5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

Streams and Fields

Below you’ll find all available data streams from Hotmart and their corresponding fields. Date fields are delivered as the Hotmart API returns them: integer epoch timestamps in milliseconds.
Stream containing historical sales data from your Hotmart products.Key Fields:
Stream containing information about recurring subscriptions.Key Fields:
Stream containing transaction history for subscriptions.Key Fields:
Stream containing commission information for sales.Key Fields:
Stream containing information about participants in sales transactions.Key Fields:
Stream containing detailed pricing information for products.Key Fields:
Stream containing information about your Hotmart products.Key Fields:
Stream containing the discount coupons configured for each of your products. Coupons are fetched per product, so this stream depends on the Products stream.Key Fields:
Stream containing information about students enrolled in your products. This stream is only available when the Members area subdomain is configured.Key Fields:

Implementation Notes

API Pagination & Limits

  • Windowed Pagination: To prevent timeouts and improve reliability when extracting large amounts of historical data, the date-filtered streams (Sales History, Sales Commission, Sales Participants, Subscriptions, Subscription Transactions and Price Details) utilize windowed pagination. The connector requests data in yearly (365-day) blocks starting from your configured Start Date up to the current date. The block size of each stream group can be changed through the Sales window, Price details window and Subscription window advanced settings.
  • Automatic Window Shrinking (504 Gateway Timeout handling): The Hotmart API can return 504 Gateway Timeout errors when a single window holds too much data. When that happens on any of the windowed streams above, the connector automatically halves the current extraction window (e.g. 365 → 182 → 91 → 45 → 30 days), rebuilds the request for the same period and retries. The reduced window is kept for the rest of the run. Only when the window is already at the minimum of 30 days and the API still times out does the stream fail, with a message pointing to the corresponding window setting.
  • Rate Limiting: Requests are throttled to the Hotmart API limit and, when a 429 Too Many Requests response is received, the connector waits for the period indicated by the API before retrying automatically.

Skills for agents

Download Hotmart skills file

Hotmart connector documentation as plain markdown, for use in AI agent contexts.