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Automate content aggregation: feed articles from Feedly into Docparser to extract key data points, then process, analyze, or store the output with custom code in Latenode. Scale document processing affordably with our execution-time pricing.
Connect Feedly and Docparser in minutes with Latenode.
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In the workspace, click the “Create New Scenario” button.

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Feedly, triggered by another scenario, or executed manually (for testing purposes). In most cases, Feedly or Docparser will be your first step. To do this, click "Choose an app," find Feedly or Docparser, and select the appropriate trigger to start the scenario.

Select the Feedly node from the app selection panel on the right.

Feedly
Next, click the plus (+) icon on the Feedly node, select Docparser from the list of available apps, and choose the action you need from the list of nodes within Docparser.

Feedly
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Docparser
Now, click the Docparser node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Docparser settings. Authentication allows you to use Docparser through Latenode.
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Use various Latenode nodes to transform data and enhance your integration:

JavaScript
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AI Anthropic Claude 3
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Docparser
Trigger on Webhook
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Feedly
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Iterator
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Webhook response
After configuring Feedly, Docparser, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Run the scenario by clicking “Run once” and triggering an event to check if the Feedly and Docparser integration works as expected. Depending on your setup, data should flow between Feedly and Docparser (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Feedly + Docparser + Slack: When a new article appears in a specified Feedly feed, Docparser fetches the document from the article URL. The parsed data is then sent to a designated Slack channel for team review and discussion.
Feedly + Docparser + Google Sheets: Upon a new article appearing in a Feedly feed, Docparser extracts key data from the article's content. This data is subsequently added as a new row in a Google Sheet for tracking and analysis.
About Feedly
Aggregate and filter Feedly articles within Latenode to automate content-driven workflows. Track brand mentions, industry trends, or competitor activity, then instantly trigger actions like posting to social media, updating databases, or notifying teams—all based on custom rules and logic.
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About Docparser
Extract data from PDFs, invoices, and forms automatically with Docparser in Latenode. Stop manual data entry. Build workflows that trigger actions based on parsed content. Use Latenode’s no-code tools to filter, transform, and route data to your database or apps, creating scalable document processing pipelines.
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How can I connect my Feedly account to Docparser using Latenode?
To connect your Feedly account to Docparser on Latenode, follow these steps:
Can I automate invoice processing from Feedly articles?
Yes, you can! With Latenode, automatically extract data from invoices linked in Feedly using Docparser, then process it using no-code blocks, JavaScript, or AI. This saves you time and reduces manual data entry.
What types of tasks can I perform by integrating Feedly with Docparser?
Integrating Feedly with Docparser allows you to perform various tasks, including:
Can I use custom JavaScript to enhance the Feedly integration?
Yes! Latenode allows you to add custom JavaScript code to your Feedly and Docparser workflows for advanced data manipulation and logic.
Are there any limitations to the Feedly and Docparser integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: