Integrate Item Lists with 500+ apps and services

This workflow shows a low code approach to parsing an XML file and storing its contents in a Google Sheets spreadsheet. To run the workflow: Make sure you are running n8n 0.197 or newer Have n8n authenticated with Google Sheets How it's done: This workflow first downloads an example file using the HTTP Request node and reads this file using the XML node. It then runs the Item Lists node to split out the individual food items from the example file. It then splits up the workflow into a separate branch creating a new spreadsheet file using the Google Sheets node. To read the column names we're using the Object.keys() method inside a Set node. Once the spreadsheet is created (the workflow waits for this using the Merge node), the data is appended to the newly created sheet (again using the Google Sheets node).

Basis workflow to convert FileMaker Data API ... to Flat File Array ...

This workflow shows a no code approach to creating Salesforce accounts and contacts based on data coming from an Excel file. For Excel 365 (the online version of Microsoft Excel) check out this workflow instead. To run the workflow: Make sure your Salesforce account is authenticated with n8n. Have a Microsoft Excel workbook with contacts and their account names ready. The workflow uses this example file, but you probably want to use your own data instead. Hit the Execute Workflow button at the bottom of the n8n canvas. Here is how it works: The workflow first searches for existing Salesforce accounts by name. It then branches out depending on whether the account already exists in Salesforce or not. If an account does not exist yet, it will be created. The data is then normalised before both branches converge again. Finally the contacts are created or updated as needed in Salesforce.

This workflow demonstrates how to export SQL to XML and present the data nicely formatted using an XSL Template. The upper part of the workflow starts with a webhook. Then it gets several random records from the SQL table and converts them into an XML string. Then a final XML file is created that contains a link to the XML Stylesheet file. The lower part of the workflow contains a helper Webhook that reads an XSL Template from the GitHub gist and serves it back via the Respond to Webhook node. This is required to comply with the CORS rules of modern browsers. These rules dictate that both XML data and a stylesheet file should come from the same domain.

This template shows how you can create reports on data in an app and share a summary in another app. Specifically, this example checks a Notion database for new submissions, filters for submissions with a specific tag, and then sends a Slack message with the number created this week. Setup instructions are located inside the workflow template.

This workflow builds a valid RSS feed (which is an XML feed under the hood) for ARD Audiothek podcasts. This allows you to subscribe to such podcasts using your favourite podcatcher without using the ARD Audiothek app. The example builds a feed for Kalk & Welk, but the workflow can be easily adjusted by providing another podcast URL on the Get overview page HTTP Request node. To subscribe to the feed, active your n8n workflow and then use the Production URL from the intitial Feed Webhook node in your podcatcher. I've tested the resulting feed using Pocket Casts... ...and Miniflux: When using Miniflux, you can add your feed via this page to your account. Make sure you select Private when doing so to avoid sharing your n8n instance with the world. The resulting feed passes the W3C Feed Validation Service: The workflow can also be used as a foundation to free other podcasts from propriertary big media platforms, though not all of them will be as simple to deal with as the ARD Audiothek.

This is Miquel from Aprende n8n and Automate with n8n. We have created a new community node Document Generator that generates dynamic content using templates. You can compose complex content with no SETs or FUNCTION ITEMs nodes using this node, like: Send one email with a list of items in the body (i.e., one email with the last entries of an RSS feed). Send one email per item (i.e., one invoice per email). Emails are just a sample. You can create complex dynamic content to: Send messages to Telegram/Slack. Create WordPress entries. Create HTML pages for your website. Create tickets. And more! The sky is your limit ;) If you want to use this workflow, install the community node n8n-nodes-document-generator from Settings > Community nodes. Type "n8n-nodes-document-generator", check "I understand the risks..." and click on "Install": Later, copy and paste this workflow into your n8n. You will get this workflow: This workflow uses the Customer Datastore node to generate sample input items. You can render one template with all items (enable "Render All Items with One Template"): or one template per input item: Visit the oficial NPM page to see more samples. Learning n8n by yourself is nice, but a bit tricky :) We offer n8n training video courses at Aprende n8n. If you need custom trainings, let us know. Additionally, you can contact us at Automate with n8n if you need the next services: Custom installations. Custom nodes. Monitor and alarms. Delegate 12/5 or 24/7 workflow issue resolutions. Automated backups of your workflows. HTTP integrations of non-supported APIs. Complex workflows. I hope you will enjoy this new node and this workflow. Automate your life! Automate it with n8n!

This workflow pushes Stripe charges to HubSpot contacts. It uses the Stripe API to get all charges and the HubSpot API to update the contacts. The workflow will create a new HubSpot property to store the total amount charged. If the property already exists, it will update the property. Prerequisites Stripe credentials. HubSpot credentials. How it works On a schedule, check if the property exists in HubSpot. If it doesn't exist, create it. The default schedule is once a day at midnight. Once property is acertained, the first Stripe node gets all charges. Once the charges are returned, the second Stripe node gets extra customer information. Once the customer information is returned, Merge data node will merge the customer information with the charges so that the next node Aggregate totals can calculate the total amount charged per contact. Once we have the total amount charged per contact, the Create or update customer node will create a new HubSpot contact if it doesn't exist or update the contact if it does exist with the total amount charged.

Use case This workflow snoozes any Todoist tasks, by moving them into a Snoozed todoist list and unsnoozes them 3 days before due date. Helps keep inbox clear only of tasks you need to worry about soon. How to setup Add your Todoist creds Create a Todoist project called snoozed Set the project ids in the relevant nodes Add due dates to your tasks in Inbox. Watch them disappear to snoozed. Set their date to tomorrow, watch it return to inbox. How to adjust this template Adjust the timeline.. Maybe 3 days is too close for you. Works mostly for me :)

This workflow shows a no code approach to creating Salesforce accounts and contacts based on data coming from Excel 365 (the online version of Microsoft Excel). For a version working with regular Excel files check out this workflow instead. To run the workflow: Make sure you have both Excel 365 and Salesforce authenticated with n8n. Have a Microsoft Excel workbook with contacts and their account names ready: Select the workbook and sheet in the Microsoft Excel node of the workflow, then configure the range to read data from: Hit the Execute Workflow button at the bottom of the n8n canvas: Here is how it works: The workflow first searches for existing Salesforce accounts by name. It then branches out depending on whether the account already exists in Salesforce or not. If an account does not exist yet, it will be created. The data is then normalised before both branches converge again. Finally the contacts are created or updated as needed in Salesforce.

How it works? This workflows sends you a monthly lists of live music events for a specific location. Events are fetched from songkick.com and delivered to you by email to a provided email address(es). Each event in the list has a link to a full SongKick page where you can see more details about the event and buy tickets for it. Example email: How to set it up? First thing that this workflow needs is a location link for your desired city from the SongKick website. You can get it by following these steps: Visit songkick.com and enter the city name in the search box: From the results page, click the result that contains the location info. These will have the Location tag on top of the location name: Once on the location page, copy the url Back in the n8n workflow page, paste the url in the location parameter of the node called Setup location and email: Second thing it needs is the email address which will receive the monthly list. For this, simply enter it in the email field of the Setup location and email node. If you want to set multiple receivers, simply separate email addresses by ,: Required accounts This workflow requires you to have a properly set up Gmail account that will be used by Gmail Node to send emails. You can read more about how to create credentials for a Gmail node in n8n documentation here.

This workflow illustrates how HTML reports can be created using Markdown Node. An example data consists of a Time Sheet table for 2 persons. Based on this table a markdown document is generated using Function Node. After that a final HTML report is created and is saved as binary file. This file can be either downloaded directly from the workflow canvas or sent as an email attachement.

This n8n workflow is designed to analyze email headers received via a webhook. The workflow splits into two main paths based on the presence of the received and authentication results headers. In the first path, if received headers are present, the workflow extracts IP addresses from these headers and then queries the IP Quality Score API to gather information about the IP addresses, including fraud score, abuse history, organization, and more. Geolocation data is also obtained from the IP-API API. The workflow collects and aggregates this information for each IP address. In the second path, if authentication-results headers are present, the workflow extracts SPF, DKIM, and DMARC authentication results. It then evaluates these results and sets fields accordingly (e.g., SPF pass/fail/neutral). The paths merge their results, and the workflow responds to the original webhook with the aggregated analysis, including IP information and authentication results. Potential issues during setup include ensuring proper configuration of the webhook calls with header authentication, handling authentication and API keys for the IP Quality Score API, and addressing any discrepancies or errors in the logic nodes, such as handling SPF, DKIM, and DMARC results correctly. Additionally, thorough testing with various email header formats is essential to ensure accurate analysis and response.

This workflow was originally presented at the February 2022 n8n Meetup. Requirements In order to use this workflow, you will need the following in place: A configured Baserow account A group in Baserow called User Empowerment Demo A database in the User Empowerment Demo called Office Shopping List Inside the Office Shopping List database, you will need two tables: Shopping List: Column 1 - Single line text column named Item Shopper: Column 1 - Single line text column named Name Column 2 - Email column named Email An email account for sending out alerts Customization To make this workflow work for you, please customize the following items: All Baserow nodes will need to be updated with your own credentials, database, tables and fields The Send Shopping List node will need to be configured with your email credentials and email addresses The Create Shopper Form Set node will need to have the code in the HTML value modified to reflect your Production URL from the Submit Shopper node (See instructions below) The Cron node will need to be modified to reflect the timing that you wish to use Modifying the Webform The webform is the piece that people normally want to customize but is often the most complex because it is raw HTML. Here are some quick tips for making changes to the form. Webform Nodes There are two nodes that control what you see in the form: Create Shopper Form - displays the form and submits it to the correct webhook Create Response Page - displays the results when the form is submitted Editing the Webform The easiest way that I have found to edit the webform is to: Open up the Set node (Create Shopper Form or Create Response Page) that contains the HTML you wish to edit. Copy the contents of the HTML value to your favourite HTML editor Make your changes Paste the updated HTML back into the Set node Changing the Webhook URL the Webform Posts To In order for the webform to work properly, do the following: Determine the Production URL for the Submit Shopper webhook node In the Create Shopper Form node, look for the following line in the HTML value: form action="https://tephlon.app.n8n.cloud/webhook/submit-shopper" method="POST" Replace https://tephlon.app.n8n.cloud/webhook/submit-shopper with your Production URL Changing the Webform Image The image that is in the webform is actually embedded in the HTML in each of the Create Shopper Form or Create Response Page Set nodes and can be modified from there using these steps: Open up the appropriate Set node In the HTML value, find the line that starts with background-image:. It will be followed by a long string that looks like random characters Using a tool like Image to Base64 Converter, upload your image and generate a new CSS background source Replace the original background-image: line (including all the "random" characters) with the new generated CSS background source

This workflow shows a no code approach to creating Salesforce accounts and contacts based on data coming from Google Sheets. To run the workflow: Make sure you have both Google Sheets and Salesforce authenticated with n8n. Have a Google Sheet with contacts and their account names ready, copy the respective sheet ID from the URL: Add the sheet ID to the Google Sheet node of the workflow: Hit Execute Workflow Here is how it works: The workflow first searches for existing Salesforce accounts by name. It then branches out depending on whether the account already exists in Salesforce or not. If an account does not exist yet, it will be created. The data is then normalised before both branches converge again. Finally the contacts are created or updated as needed in Salesforce.

This workflow generates CSV files containing a list of 10 random users with specific characteristics using OpenAI's GPT-4 model. It then splits this data into batches, converts it to CSV format, and saves it to disk for further use. The execution of the workflow begins from here when triggered manually. "OpenAI" Node. This uses the OpenAI API to generate random user data. The input to the OpenAI API is a fixed string, which asks for a list of 10 random users with some specific attributes. The attributes include a name and surname starting with the same letter, a subscription status, and a subscription date (if they are subscribed). There is also a short example of the JSON object structure. This technique is called one-shot prompting. "Split In Batches" Node. This node is used to handle the OpenAI responses one by one. "Parse JSON" Node. This node converts the content of the message received from the OpenAI node (which is in string format) into a JSON object. "Make JSON Table" Node. This node is used to convert the JSON data into a tabular format, which is easier to handle for further data processing. "Convert to CSV" Node. This node converts the table format data received from the "Make JSON Table" node into CSV format and assigns a file name. "Save to Disk" Node. This node is used to save the CSV generated in the previous node to disk in the ".n8n" directory. The workflow is designed in a circular manner. So, after saving the file to disk, it goes back to the "Split In Batches" node to process the OpenAI output, until all batches are processed.

This n8n workflow automates the handling of security detections from CrowdStrike, streamlining incident response and notification processes. The workflow is triggered daily at midnight by the Schedule Trigger node. It begins by fetching recent security detections from CrowdStrike using an HTTP Request node. The response is then split into individual detections for further processing. Each detection is enriched by querying the CrowdStrike API for detailed information using another HTTP Request node. The workflow then processes these detections sequentially using the Split In Batches node. Next, it looks up behavioral information associated with each detection in VirusTotal using two HTTP Request nodes. One node queries VirusTotal based on SHA256 values, and the other based on IOC (Indicator of Compromise) values. The workflow includes a 1-second pause using the Wait node to prevent rate limiting when making requests to the VirusTotal API. Subsequently, the workflow sets fields with relevant details from both CrowdStrike and VirusTotal, including detection links, confidence scores, filenames, usernames, and more. These details are concatenated using an Item Lists node for each detection. The final step involves creating Jira issues for each detection, including summaries with CrowdStrike alert severity and hostnames, as well as descriptions that incorporate information from CrowdStrike and VirusTotal. Information about this issue is then sent via a Slack message to a Slack user. Potential issues during setup might include configuring the Schedule Trigger node to trigger at the correct time zone and handling potential rate limiting from the VirusTotal API, which could lead to throttled requests. Additionally, the note about a possible typo in the URL for the Virustotal nodes should be addressed to ensure correct API calls. The Jira node may need to be replaced with the latest version for compatibility. Properly configuring API credentials and handling errors that may occur during API requests are essential for a smooth workflow operation. Careful testing with sample data is recommended to validate the workflow's functionality and ensure it aligns with your organization's security incident response processes.

This workflow combines customers' details with their payment data and passes the input to Pipedrive as a note to the organization. Prerequisites Stripe account and Stripe credentials Pipedrive account and Pipedrive credentials How it works Cron node triggers the workflow every day at 8 a.m. HTTP Request node searches for payments in Stripe. The Item Lists node creates separate items from a list of payment data. Merge node takes in the payment data as an input 1. Stripe node gets all the customers data. Set node renames customer-related data fields and keeps only needed fields. Merge node takes in the customer data as an input 2. Merge node combines the payment data with the customers one. Pipedrive node searches for the organization and creates a note with payment data.

This workflow uses a Mautic Trigger to check for new contacts. It then validates the contacts' email using OneSimpleAPI. If there are any a message will be sent to Slack. To configure this workflow you will need to set the credentials for the Hubspot, OneSimpleAPI and Slack Nodes. You will also need to select the Slack channel to use for sending the message.

This workflow adds a new product in Stripe whenever a new product has been added to Pipedrive. Prerequisites Stripe account and Stripe credentials Pipedrive account and Pipedrive credentials How it works Pipedrive trigger node starts the workflow when a new product is added. HTTP Request node creates a new product in Stripe using previuos input. Merge node combines data of both Pipedrive and Stripe inputs. The output will contain the data of Pipedrive input merged with the data of Stripe input. The merge occurs based on the index of the items. The Item Lists node splits prices to separate items. HTTP Request node creates price records in Stripe.

This workflow demonstrates two ways of exporting data from SQL to XML. First, several random records are received from the MySQL database. Then, in the upper part of the workflow, the structure of an XML is defined in the Set node. After that, the ItemLists node combines all items into an array. This allows an XML node to create a simple XML file. The lower part of the workflow shows how to create an XML with attributes. It is almost identical except that a $ (dollar sign) JSON key is used to define XML attributes. Finally, both files are saved locally.

Get recent funding rounds from Crunchbase in Google Sheets, along with 10+ data points (LinkedIn URL, monthly traffic, company size, etc.) You’ll be able to: Create a custom database Reach out to interesting leads at the right time Send custom alerts to your tools This workflow scrape recent funding rounds from Crunchbase, and add them in Google Sheets. It uses Piloterr API to get this data with ease. Full guide can be found here: https://lempire.notion.site/Get-recent-fundraising-in-Google-Sheets-dafbbda2635544b4925c4fb04abac8f5?pvs=74

This tutorial demonstrates the creation of the HTML report via Markdown node. The main idea is to prepare a very long gext variable via the Function Node and then convert it to the HTML file. The resulting report can be downloaded from the workflow canvas directly or send via email as an attachment.

The workflow automates the process of creating a summarized and enriched podcast digest, which is then sent via email. Note that to use this template, you need to be on n8n version 1.19.4 or later.

This n8n workflow serves as a powerful cybersecurity and threat intelligence tool to look up URLs or IP addresses through industry standard threat intelligence vendors. It starts with either a form submission or a webhook trigger, allowing users to input data, URLs or IPs that require analysis. The workflow then splits into two paths depending on whether the input data is an IP or URL. If an IP was given, it sets the ip variable to the IP; however if a URL was given the workflow will perform a DNS lookup using Google Public DNS and sets the ip variable based on the results from Google. The workflow then checks the obtained IP addresses against GreyNoise services, with one branch utilizing GreyNoise RIOT IP Lookup to assess IP reputation and association with known benign services, and the other using GreyNoise IP Context to evaluate potential threats. The results from both GreyNoise services are merged to create a comprehensive analysis which includes the IP, classification (benign, malicious, or unknown), IP location, tags to identify activity or malware, category, and trust level. In parallel, a VirusTotal scan is initiated for the URL/IP to identify if it is malicious. A 5-second wait ensures proper processing, and the workflow subsequently polls the scan result to determine when the analysis is complete. The workflow then summarizes the analysis including the overall security vendor analysis results, blockList analysis, OpenPhish analysis, the URL, and the IP. Finally, the workflow combines the summarized intelligence from both GreyNoise and VirusTotal to provide a thorough analysis of the URL/IP. This summarized intelligence can then be emailed to the user that filled out the form via Gmail or it can be sent to the user via a Slack message. Setting up this workflow may require proper configuration of the form submission or webhook trigger, and ensuring that the GreyNoise and VirusTotal API credentials are correctly integrated. Users should also consider the potential volume of data and API rate limits, as excessive requests could lead to issues. Proper documentation and validation of input data are crucial to ensure accurate and meaningful results in the final report.

Send a simple JSON array via HTTP POST and get an Excel file. The default filename is Export.xlsx. By adding the (optional) request ?filename=xyz you can specify the filename. NOTE: do not forget to change the webhook path!

This workflow syncs Zendesk tickets to Pipedrive contact owners. This workflow is triggered every day at 09:00 with Zendesk collecting all the tickets updated after the last execution timestamp and updating them according to Pipedrive contacts. It also adds Zendesk comments to the tickets as notes in Pipedrive. Prerequisites Pipedrive account and Pipedrive credentials Zendesk account and Zendesk credentials Note: The Pipedrive and the Zendesk accounts need to be created by the same person / with the same email. How it works Cron node triggers the workflow every day at 09:00. Zendesk node collects all the tickets updated after the last execution timestamp. If node checks if the channel in the ticket is an email, and if so, it continues the workflow. The Item Lists node removes duplicates to make search efficient. Pipedrive node searches persons by email. Set node renames and keeps only needed fields (email & person id) Merge by key node adds the Pipedrive contact id to Zendesk tickets. The HTTP Request node gets Zendesk comments for tickets and the Merge node adds them to tickets. Split node adds nodes in batches with each iteration. Item list node splits comments into separate items. Pipedrive node adds comment as notes. If node checks if the data processing is done and if not, goes back to the Split node. The Function Item node sets the new last execution timestamp.

You still can use the app in a workflow even if we don’t have a node for that or the existing operation for that. With the HTTP Request node, it is possible to call any API point and use the incoming data in your workflow Main use cases: Connect with apps and services that n8n doesn’t have integration with Web scraping How it works This workflow can be divided into three branches, each serving a distinct purpose: 1.Splitting into Items (HTTP Request - Get Mock Albums): The workflow initiates with a manual trigger (On clicking 'execute'). It performs an HTTP request to retrieve mock albums data from "https://jsonplaceholder.typicode.com/albums." The obtained data is split into items using the Item Lists node, facilitating easier management. 2.Data Scraping (HTTP Request - Get Wikipedia Page and HTML Extract): Another branch of the workflow involves fetching a random Wikipedia page using an HTTP request to "https://en.wikipedia.org/wiki/Special:Random." The HTML Extract node extracts the article title from the fetched Wikipedia page. 3.Handling Pagination (The final branch deals with handling pagination for a GitHub API request): It sends an HTTP request to "https://api.github.com/users/that-one-tom/starred," with parameters like the page number and items per page dynamically set by the Set node. The workflow uses conditions (If - Are we finished?) to check if there are more pages to retrieve and increments the page number accordingly (Set - Increment Page). This process repeats until all pages are fetched, allowing for comprehensive data retrieval.

This workflow allows to scrape Google Maps data in an efficient way using SerpAPI. You'll get all data from Gmaps at a cheaper cost than Google Maps API. Add as input, your Google Maps search URL and you'll get a list of places with many data points such as: phone number website rating reviews address And much more. Full guide to implement the workflow is here: https://lempire.notion.site/Scrape-Google-Maps-places-with-n8n-b7f1785c3d474e858b7ee61ad4c21136?pvs=4

This workflow imports multiple CSV files and appends or updates them to a Google Sheets document. Here's a step-by-step breakdown: When clicked "Execute Workflow", the process starts. The "Read Binary Files" node reads all the '.csv' files from the specified directory. The files are then split into batches (one file in a batch) by the "Split In Batches" node. For each file, the "Read CSV" node reads the data from the CSV file. The "Assign source file name" node assigns the source file name to the data. The data is then processed by the "Remove duplicates" node. This removes any duplicate entries based on the 'user_name' field. The "Keep only subscribers" node filters the data to keep only those entries where the 'subscribed' field is set to 'TRUE'. The data is then sorted by the 'date_subscribed' field using the "Sort by date" node. Finally, the processed data is appended or updated to a specified Google Sheets document using the "Upload to spreadsheet" node. It checks for the 'user_name' field, if the data corresponding to that 'user_name' already exists, it updates the data, otherwise appends the new data.

This is an example workflow that imports an XML file into an SQL database. The ReadBinaryFiles node loads the XML file from the server. Then the Code node extracts the file content from the binary buffer. Afterwards, an XML node converts the XML string into a JSON structure. Finally, in the MySQL node inserts the data records into the SQL table. In the upper part of the workflow there is another MySQL node that is disabled. This node creates a new table with all the required variables based on the sample SQL database: https://www.mysqltutorial.org/mysql-sample-database.aspx

The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.

The News Site from Colt, a telecom company, does not offer an RSS feed, therefore web scraping is the choice to extract and process the news. The goal is to get only the newest posts, a summary of each post and their respective (technical) keywords. Note that the news site offers the links to each news post, but not the individual news. We collect first the links and dates of each post before extracting the newest ones. The result is sent to a SQL database, in this case a NocoDB database. This process happens each week thru a cron job. Requirements: Basic understanding of CSS selectors and how to get them via browser (usually: right click → inspect) ChatGPT API account - normal account is not sufficient A NocoDB database - of course you may choose any type of output target Assumptions: CSS selectors work on the news site The post has a date with own CSS selector - meaning date is not part of the news content "Warnings" Not every site likes to be scraped, especially not in high frequency Each website is structured in different ways, the workflow may then need several adaptations.

Use Case Automatically archive emails in your Gmail inbox from the last day, unless they have been starred. Been using this with my personal and work emails to stick to an Inbox Zero strategy, without having to click or swipe a lot. Setup Add your Gmail creds How to adjust this template Set your own schedule for when to run this. Otherwise, should be good to go. 🤞🏽

This workflow enriches new accounts in Pipedrive using Datagma API by adding data about ICP (ideal customer profile). Instead of Pipedrive, you can use any other CRM. In this example, ideal buyers are heads of sales/business development. Prerequisites Pipedrive account and Pipedrive credentials How it works Pipedrive trigger node starts the workflow when a new company is created. HTTP Request node queries data from Datagma. Pipedrive node updates Pipedrive contact with new data from Datagma. The Item Lists node simplifies returned data from Datagma that contain lists (arrays), enabling you to easily modify the structure for further processing without the need to use Function nodes and write custom JavaScript. IF node identifies if the lead corresponds ICP. HTTP Request node searches for emails in Datagma. Set node prepares data for further merging. Merge node combines data from multiple streams. Pipedrive node adds a new person in Pipedrive.

Usage This workflow gets all the posts from your WordPress site and sorts them into a clear format before publishing them to medium. Step 1. Set up the HTTP node and set the URL of the source destination. This will be the URL of the blog you want to use. We shall be using https://mailsafi.com/blog for this. Step 2. Extract the URLs of all the blogs on the page This gets all the blog titles and their URLs. Its an easy way to sort ou which blogs to share and which not to share. Step 3. Split the entries for easy sorting or a cleaner view. Step 4. Set a new https node with all the blog URLs that we got from the previous steps. Step 5. Extract the contents of the blog Step 6. Add the medium node and then set the contents that you want to be shared out. Execute your workflow and you are good to go