Navigating the realm of APIs and web scraping is no easy feat, especially when dealing with pagination. Pagination is the process of dividing large datasets into smaller, more digestible chunks, which is essential for improved user experience. Owing to server load and data transmission concerns, APIs often limit the number of items returned in a single response. That’s where n8n, an open-source workflow automation tool, comes to the rescue. In this comprehensive guide, we’ll delve into looping through paginated API responses using n8n.

Understanding the World of Pagination

Before we get our hands dirty with n8n, it’s crucial to comprehend the pagination concept. APIs and web pages typically utilize some form of pagination to manage data. Three main types of pagination exist:

  • Offset-based pagination: The API provides an ‘offset’ parameter for specifying the starting point and a ‘limit’ parameter to control the number of items returned.
  • Page-based pagination: The API employs a ‘page’ parameter to navigate through the dataset and a ‘size’ parameter to control the number of items returned.
  • Cursor-based pagination: The API offers a ‘cursor’ (usually a unique identifier or timestamp) to fetch the next set of items.

Identifying the pagination type used by your target API is vital for implementing the appropriate looping logic.

Getting Started with n8n

To jump into n8n, follow these simple steps:

  • Install n8n on your local machine or server using Docker or npm (Node.js package manager).
  • Launch the n8n editor by running the n8n start command or accessing the web interface.
  • Create a new workflow by clicking the “+” button in the top right corner of the editor.

Crafting the Initial API Request

In your new workflow, add an “HTTP Request” node to make the first API request:

  • Click on the “+” button and search for the “HTTP Request” node.
  • Configure the node by setting the appropriate request method (e.g., GET), URL, and required authentication (if necessary).
  • Consult the API documentation to pinpoint the pagination parameters required for the request, such as ‘offset’, ‘limit’, ‘page’, ‘size’, or ‘cursor’.
  • Execute the node by clicking the “Execute Node” button.

Looping Your Way Through Pagination

To loop through the paginated API response, adhere to these steps:

  • Add a “Function” node to the workflow to determine the total number of pages or iterations needed based on the API response.
  • Use a “Variable” node to store the current page or iteration number.
  • Implement a “Loop” node to repeatedly make API requests, incrementing the page or iteration number each time.
  • Within the loop, add another “HTTP Request” node configured with the updated pagination parameters.
  • Utilize a “Merge” node to combine data from all API requests into a single dataset.

Handling the Data with Precision

After looping through the pagination, you can process the collected data as desired:

  • Use “Function” nodes to transform or filter the data.
  • Add “Database” nodes to store the data in your preferred database or data warehouse.
  • Implement “Webhook” nodes to send the data to other applications or services.

Executing the Workflow

Once you’ve polished the workflow, run it by clicking the “Execute Workflow” button. Keep an eye on your workflow’s progress in the “Execution Log” panel and examine the final dataset in the “Output Data” panel.


Efficiently handling paginated data in your workflows is now possible, thanks to n8n. By mastering pagination fundamentals, setting up n8n, and implementing looping logic, you can access and process large datasets from APIs and web pages with ease. n8n’s flexibility and extensibility enable seamless integration with your existing data pipeline, allowing you to work with voluminous data without any hassles.

It’s important to always review the API documentation and rate limits imposed by the provider to ensure compliance and avoid potential issues. As you become more adept at using n8n, explore its rich ecosystem of nodes and integrations to further enhance your data processing and automation capabilities.

Happy automating!

Disclaimer: The code snippets and examples provided on this blog are for educational and informational purposes only. You are free to use, modify, and distribute the code as you see fit, but I make no warranties or guarantees regarding its accuracy or suitability for any specific purpose. By using the code from this blog, you agree that I will not be held responsible for any issues or damages that may arise from its use. Always exercise caution and thoroughly test any code in your own development environment before using it in a production setting.

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