Workflow Templates

Complete MCP server exposing 1 Listing API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Listing API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Listing API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath} • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 Item_Draft (1 endpoints) • POST /item_draft/: Create eBay Listing Draft 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Listing API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Proxy Detection by IP2Proxy - MCP Server

by David Ashby

Complete MCP server exposing 1 IP2Proxy Proxy Detection API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add IP2Proxy Proxy Detection credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the IP2Proxy Proxy Detection API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ip2proxy.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 General (1 endpoints) • GET /: Check Proxy IP 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native IP2Proxy Proxy Detection API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

AI Image Nudity Detection Tool with Image Moderation API

by David Ashby

Complete MCP server exposing 1 Image Moderation API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Image Moderation credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Image Moderation API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.moderatecontent.com/moderate/ • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 endpoints) General (1 operation) Detect Nudity in Images 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Image Moderation API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Track n8n Workflow Changes Over Time with Compare Dataset & Google Sheets

by Jimleuk

This n8n template runs daily to track and report on any changes made to workflows on any n8n instance. Useful if a team is working within a single instance and you want to be notified of what workflows have changed since you last visited them. Another use-case might be monitoring your managed instances for clients and being alerted when changes are made without your knowledge. See a sample Gsheet here: https://docs.google.com/spreadsheets/d/1dOHSfeE0W_qPyEWj5Zz0JBJm8Vrf_cWp-02OBrA_ZYc/edit?usp=sharing How it works A scheduled trigger is set to run once a day to review all available workflows. An n8n node imports the workflows as json. The workflows are brought into a loop where each is first checked to see if it exists in the designated google sheet. If not, a new entry is created and skipped. If the workflow has been captured before, then the comparison subworkflow can be executed using the previous and current versions of the workflow json data. The subworkflow uses the compare dataset tool to calculate the changes to nodes and connections for the given workflow. The results are then recorded back to the google sheet for review. How to use Start with the n8n node and try to filter by the workflows you're interested in tracking. Set the scheduled trigger interval to match the frequency to suit how often your workflows are being edited. Customising the workflow Want to get fancy? Add in an AI agent to help determine changes between the previous and current versions of the workflow. Add contextual explanations to reveal the impact of the changes.

Send or update new Mailchimp subscribers in HubSpot

by n8n Team

This workflow sends new Mailchimp subscribers to HubSpot as new or updated contacts. Prerequisites Mailchimp account and Mailchimp credentials HubSpot account and HubSpot credentials How it works Cron node triggers this workflow every day at 7:00. Mailchimp node searches for new subscribers. New Mailchimp subscribes get sent to HubSpot. HubSpot node either updates the existing contact or adds a new one to the pipeline.

2 nodes1076 views

Sync tasks automatically from Todoist to Notion

by n8n Team

This workflow checks if the task in Todoist has a specific label and based on that creates a new database page in Notion. Prerequisites Todoist account and Todoist credentials Notion account and Notion credentials How it works To start the workflow add a task to Todoist and mark it with a label, e.g. “send-to-n8n”. Wait a maximum of 30 seconds. Todoist node identifies the tasks marked as “send-to-n8n”. Notion node creates a new Notion database page. Notice Notion has a new task now with the same name as in Todoist.

🤖AI & Machine Learning

2 nodes5459 views

N8N Advanced URL Parsing and Shortening Workflow - Switchy.io Integration

by Nskha

Overview This N8N workflow facilitates advanced URL parsing and shortening, incorporating metadata extraction, OpenGraph tag handling, and integration with Switchy API for link management. It employs various nodes for URL processing, metadata extraction, and creation or updating of shortened links with enriched metadata. Features URL Metadata Extraction:** Parses URLs to extract metadata such as titles, descriptions, images, and favicons. OpenGraph API Integration:** Utilizes OpenGraph API for detailed metadata retrieval. Switchy API Integration:** Manages shortened links via the Switchy API. GitHub API Integration:** Uses GitHub for hosting images related to the URLs. Screenshot Capabilities:** Captures screenshots of web pages as part of metadata. API Authorization and Configuration:** Manages API keys and configurations for external service integration. Workflow Structure Split In Batches: Processes URLs in batches. API Auth: Configures API authorization. URL Processing Nodes: Extract metadata using various nodes like Get Headers, OpenGraph API, and Meta tags Scraper. Conditional Nodes: Include IF OpenGraph Invalid and If - Enable ScreenShots for logic handling. Data Aggregation: Uses nodes like Method 1 - META for final metadata aggregation. Switchy API: Handles link creation and updating. GitHub Integration: Hosts screenshots and images on a personal GitHub repository. Final Output: Provides the shortened URL after processing. API Stack | API | Description | |---------------------------------|-------------------------------------------------| | switchy | For creating and updating shortened links. | | opengraph | To retrieve URL metadata using OpenGraph tags. | | dub.sh | Used for scraping meta tags from web pages. | | microlink | Captures screenshots of web pages. | | pxl.to | Alternative service for capturing screenshots. | | favicone | Retrieves favicons for given URLs. | | github | Hosts images and screenshots on GitHub repo. | | statically | Used for CDN services and image hosting. | | Other APIs | Additional APIs used for various purposes. | GitHub Repository Setup To use this workflow, ensure your GitHub API is linked for hosting images. Set up a repository where the workflow can upload screenshots and other related images. This repository will be referenced in the workflow nodes where images are handled. Configuration Before running the workflow, set up the necessary API keys and configurations in the API Auth node. Adjust batch size and other parameters as needed. Error Handling The workflow includes nodes like Stop and Error for robust error handling, post an issue and mention the creator using N8N community. Contributions This workflow is open for community contributions. Enhancements and improvements are welcome.

Get Multiple Attachments from Gmail and upload them to GDrive

by Ria

This is a simple template to show how to extract multiple email attachments and return them as an iterable output. How it works: The Gmail Trigger node detects any new email that has attachments. The Code node will then extract them as binary files and attaches them to the item. They can then be uploaded via the Google Drive node. Setup steps: add your Gmail Credentials add your Google Drive Credentials Follow the official n8n Documentation for help Feedback & Questions If you have any questions or feedback about this workflow - Feel free to get in touch at ria@n8n.io

1 nodes7966 views

Create Snapshot of Contabo VPS instances on a daily basis

by DUBCOM

Workflow: Snapshot Contabo How it Works This workflow automates daily backups (snapshots) of VPS instances hosted on Contabo. Each day at midnight, it checks for existing snapshots and ensures that only the latest backups are retained by removing older ones. It provides a seamless, hands-off backup process to keep your data secure. Setup Steps Setting up this workflow is quick, typically taking about 10-15 minutes. The essential part of the setup is providing the necessary credentials, which you can easily retrieve from your Contabo control panel. Import the Workflow: Download and upload the workflow JSON into n8n. Configure Credentials: Add CLIENT_ID, CLIENT_SECRET, API_USER, and API_PASSWORD in the credential node. Activate the Workflow: Enable it to run automatically at midnight every day. Flow Overview Schedule Trigger (00:00 daily):** Automatically initiates the workflow. Formatted Date:** Prepares a timestamp for naming the snapshot. List Snapshots:** Verifies if an existing snapshot is available for each VPS. Conditional Logic:** No Snapshot? Proceeds to create a new one. Snapshot Found? Deletes the old snapshot before creating a new one. Key Points Snapshot Retention:** Old snapshots are deleted to ensure only the latest backups are stored. Unique Identifiers:** UUIDs are used to track and guarantee unique operations.

Auto Categorise Outlook Emails with AI

by Wayne Simpson

Automate your email management with this workflow, designed for freelancers and business professionals who receive high volumes of emails. By leveraging AI-powered categorisation and dynamic email processing, this template helps you organise your inbox and streamline communication for better efficiency and productivity. Check out the YouTube video for step-by-step set up instructions! How it works: Fetch & Filter Emails: The workflow retrieves emails from your Microsoft Outlook account, filtering out flagged emails and those already categorised. Content Preparation: Each email is cleaned up and converted to a structured format using Markdown, making it easier for AI processing. AI Categorization: The content is analysed using an AI model, which categorises the emails into predefined categories (e.g., Action, Junk, Business, SaaS) based on the context and content. Email Categorization & Folder Management: The categorised emails are updated in Microsoft Outlook and moved to respective folders such as "Junk Email" or "Receipts" based on the AI's classification. Conditional Processing & Final Checks: Additional checks and conditions ensure that only unread emails are processed, and errors are gracefully managed to maintain workflow stability. Set up steps: Connect Microsoft Outlook: Link your Microsoft Outlook account using the built-in credentials node to enable email fetching, updating, and folder management. Configure AI Model (Ollama API): Set up the AI model by connecting to the Ollama API and choosing your desired language model for categorisation. Modify Email Categories (Optional): Customize the categories and subcategories within the workflow to suit your unique email management needs. Set Up Error Handling: Review the error handling node settings to ensure smooth workflow execution. This template offers a robust solution for managing and organising your inbox, helping you save time and keep your focus on important emails.

3 nodes38586 views

Automate Droplet Snapshots on DigitalOcean

by Darryn Balanco

This workflow automates the management of DigitalOcean Droplet snapshots by listing all droplets, filtering based on the number of snapshots, and deleting excess snapshots before creating new ones. It ensures your droplet snapshots stay organized and within a manageable limit, preventing unnecessary storage costs due to an excess of snapshots. Who is this for? This workflow is perfect for users managing DigitalOcean Droplets and looking to automate the process of snapshot creation and cleanup to save on storage costs and maintain efficient resource management. It’s useful for DevOps teams, cloud administrators, or any developer leveraging DigitalOcean for their infrastructure. What problem is this workflow solving? When managing multiple DigitalOcean Droplets, snapshots can quickly accumulate, taking up space and increasing storage costs. Manually deleting and creating snapshots can be time-consuming and inefficient. This automation solves this problem by automating the snapshot management process, ensuring that no more than a defined number of snapshots are kept per droplet. What this workflow does Runs every 48 hours: The workflow is triggered by a cron node that runs every 48 hours, ensuring timely snapshot management. List all droplets: The workflow retrieves all droplets in the DigitalOcean account. Retrieve snapshots: For each droplet, the workflow retrieves a list of existing snapshots. Filter snapshots: If the number of snapshots exceeds 4, the workflow filters for snapshots that need to be deleted. Delete snapshots: Excess snapshots are automatically deleted based on the filter criteria. Create new snapshot: After cleaning up, the workflow creates a new snapshot for each droplet, ensuring that backups are always up-to-date. Setup DigitalOcean API Key: You’ll need to configure the HTTP Request nodes with your DigitalOcean API key. This key is required for authenticating requests to list droplets, retrieve snapshots, delete snapshots, and create new ones. Snapshot Threshold: By default, the workflow is set to keep no more than 4 snapshots per droplet. This can be adjusted by modifying the filter node conditions. Set Execution Frequency: The cron node is set to run every 48 hours, but you can adjust the timing to suit your needs. How to customize this workflow Adjust Snapshot Limit**: Change the value in the filter node if you want to keep more or fewer snapshots. Modify Run Frequency**: The workflow runs every 48 hours by default. You can change the frequency in the cron node to run more or less often. Enhance with Notifications**: You can add a notification node (e.g., Slack or email) to alert you when snapshots are deleted or created. Workflow Summary This workflow automates the management of DigitalOcean Droplet snapshots by keeping the number of snapshots under a defined limit, deleting the oldest ones, and ensuring new snapshots are created at regular intervals.