This workflow takes a text file as input. It pulls the information from the text file and used it as a parameter to execute a command for each text line. This workflow references a file /home/n8n/filelist.txt in the Read Binary File node which will need to be changed to work properly. You can also edit the Execute Command node to modify what happens for each of these lines of text. Note: This workflow requires the Execute Command node which is only available on the on-premise version of n8n.
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See all General Automation→Tiny tiny Rss (aka tt-rss) Feed to Mastodon
Every 10 minutes look at your published news in your Tiny tiny RSS public feed and make a toot on your mastodon. You'll need: Your mastondon URL instance Your mastondon access token Your Tiny Tiny RSS public published feed URL
Solve PopularCaptcha image challenges with CaptchaSonic via webhook
Quick Overview This workflow receives a PopularCaptcha image challenge via webhook or manual test input, sends it to CaptchaSonic for recognition/classification, and returns the solved result as JSON to the caller or as formatted output for testing. How it works Receives a POST webhook request containing a base64 image, question, websiteURL, and optional extra fields. Sends the challenge details to CaptchaSonic using the PopularCaptcha image recognition/classification operation. Returns CaptchaSonic’s solution data as a JSON webhook response. Optionally, runs a manual test path that loads sample image/question data and submits it to CaptchaSonic. Formats the manual test output by stringifying the solution data and adding a status and timestamp. Setup Install the n8n-nodes-captchasonic community node in your n8n instance. Create and select a CaptchaSonic credential with your CaptchaSonic API key. If using the webhook path, copy the production webhook URL for /solve-popularcaptcha and configure your client to POST image, question, websiteURL, and optionally extraFields in the request body. If needed, replace the hardcoded sample data in the manual test input to match your PopularCapt
Upload CSV test cases to Qase and send completion alerts to Slack
Quick overview This workflow upload test cases from a CSV file into Qase App and sends a confirmation message to your Slack channel. How it works Receives a form submission containing a public CSV URL and a selected Qase project option. Downloads the CSV file from the provided URL and extracts its rows into individual test-case items. Maps each row into the JSON payload Qase expects (including project code, fields like severity/priority/type, and optional parsed steps). Creates the test cases in Qase by sending a POST request per item to the Qase Cases API for the mapped project. Aggregates the upload responses into a single result. Sends a Slack incoming-webhook message confirming the test case upload is complete. Setup Create a Qase API token and add it to the Qase HTTP Header Auth credentials used for the Qase API request. Create a Slack Incoming Webhook, paste the webhook URL into the Slack notification HTTP request node, and customize the message text if needed. Ensure the uploaded CSV is publicly accessible via URL and uses the expected columns (for example: title, description, preconditions, postconditions, severity, priority, type, layer, behavior, automation, and optional