by David Ashby
Complete MCP server exposing 1 Article Search 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 Article Search 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 Article Search 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 http://api.nytimes.com/svc/search/v2 • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 Articlesearch.Json (1 endpoints) • GET /articlesearch.json: Search Articles 🤖 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 Article Search 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.
by Angel Menendez
Who’s it for This template is perfect for OMI pendant users or anyone with AI-generated memory transcripts who want to: Automatically create daily journals in Markdown Extract actionable tasks from conversations Store memories in Google Drive Sync action items to Google Tasks Great for creators, ADHD professionals, techies, or productivity hackers who want to build a second brain workflow with no manual data entry. What it does / How it works This workflow: Accepts POST data from the OMI AI pendant (via webhook) Extracts structured summaries, tasks, events, and raw transcript data Converts the transcript into Markdown using metadata like emoji, category, and overview Uses Google Gemini or an AI Agent to generate a high-quality journal entry Splits out action items and creates tasks in Google Tasks Uploads both the transcription and the final journal file into separate Google Drive folders for archival Deletes processed files if needed (cleanup path is included) How to set up Connect your OMI device to send daily summaries to the webhook endpoint Authenticate your Google Drive and Google Tasks accounts Replace any hardcoded values (like folder IDs or task list IDs) with your own Review the system prompt in the AI Agent node if you'd like to personalize your journal style ## Requirements OMI pendant or device that generates .md summaries via API or webhook Google Drive & Google Tasks credentials set up in n8n Optional: Google Gemini or OpenAI for natural language journal generation ## How to customize Change the output folder IDs for GDrive in the Upload Transcription and Upload Journal nodes. One folder is for long term storage and the other is short term, the contents of which are deleted every night to generate the journal entries. Ensure your workflow timezone is set correctly in the settings. Replace Google Tasks with another todo app (e.g. Notion, Todoist) using HTTP or native nodes Customize the AI prompt in the AI Agent or Gemini Chat node to reflect your tone (e.g., poetic, minimalist, spiritual) Modify the Markdown format in the Build Markdown Transcription node for your preferred structure
by Artem Boiko
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. CAD-BIM Multi-Format Validation Pipeline This workflow enables automated validation of CAD and BIM files in multiple formats (Revit, IFC, DWG, DGN) for compliance with project standards and requirements. Key Features Converts Revit, IFC, DWG, and DGN models into open data tables Runs automated validation checks on model naming, structure, attributes, and completeness Generates error reports and QTO (Quantity Take-Off) tables for all processed files How it works Upload one or more project files in Revit (.rvt), IFC (.ifc), DWG, or DGN formats The pipeline automatically processes each file and validates against configurable rules in Excel form Error summaries and QTO tables are generated All outputs are available for download as Excel Converter Path:** Make sure the converter executable (e.g. RvtExporter.exe) is placed in DDC Exporter\datadrivenlibs\. Specify the full path in the workflow settings if required. Troubleshooting:** If conversion fails, double-check the path to the executable. Only supported formats can be processed (see GitHub Readme). Review logs in /output for error details. Docs & Issues:** Full Readme on GitHub
by Marcial Ambriz
Remixed Backup your workflows to GitHub from Solomon's work. Check out his templates. How it works This workflow will backup your typebots to GitHub. It uses the Typebot API to export all typebots. It then loops over the data, checks in GitHub to see if a file exists that uses the credential's ID. Once checked it will: update the file on GitHub if it exists; create a new file if it doesn't exist; ignore if it's the same. In addition, it also checks if any flow have been deleted from typebot workspace. If a flow no longer exists in workspace, the corresponding file will be removed from the repository to keep everything in sync. Who is this for? People wanting to backup their typebots(flows) outside the server for safety purposes or to migrate to another server.
by Gregor
This workflow offers several additional features for time tracking with Awork: Check whether time has been tracked when closing a task. If not, the task is reopened and the user is notified. This can be restricted to specific tasks using tags. Enforce a minimum time entry for tasks to comply with "at least 15-minute intervals are billed" policies. This can also be limited to specific tasks by using tags. Clean up time entries to match billing intervals. Add a start time to time entries if it is missing. This workflow does not use the Awork community nodes package, as the package does not support all required API calls and is therefore not used here. If you prefer to use that package, you can find more information at awork integration guide and replace the HTTP nodes with the corresponding community nodes where applicable. How it works Triggered via Awork Webhook call on status change of tasks and new time entries Set up steps Add webhook call to Awork (please see in-workflow notes regarding webhook configuration) Configure Awork API credentials Set up workflow configuration via setup node, e.g. user notification text, tags, enabled features etc.
by David Ashby
Complete MCP server exposing all PagerDuty Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built. ⚡ 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 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 • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every PagerDuty Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n PagerDuty Tool tool with full error handling 📋 Available Operations (9 total) Every possible PagerDuty Tool operation is included: 🔧 Incident (4 operations) • Create an incident • Get an incident • Get many incidents • Update an incident 🔧 Incidentnote (2 operations) • Create an incident note • Get many incident notes 🔧 Logentry (2 operations) • Get a log entry • Get many log entries 👤 User (1 operations) • Get a user 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native PagerDuty Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every PagerDuty Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.
by David Ashby
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.
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.
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.
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.
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.
by Madame AI
Synchronize WooCommerce Inventory & Create Products with Gemini AI & BrowserAct This sophisticated n8n template automates WooCommerce inventory management by scraping supplier data, updating existing products, and intelligently creating new ones with AI-formatted descriptions. This workflow is essential for e-commerce operators, dropshippers, and inventory managers who need to ensure their product pricing and stock levels are synchronized with multiple third-party suppliers, minimizing overselling and maximizing profit. Self-Hosted Only This Workflow uses a community contribution and is designed and tested for self-hosted n8n instances only. How it works The workflow is typically run by a Schedule Trigger (though a Manual Trigger is also shown) to check stock automatically. It reads a list of suppliers and their inventory page URLs from a central Google Sheet. The workflow loops through each supplier: A BrowserAct node scrapes the current stock and price data from the supplier's inventory page. A Code node parses this bulk data into individual product items. It then loops through each individual product found. The workflow checks WooCommerce to see if the product already exists based on its name. If the product exists: It proceeds to update the existing product's price and stock quantity. If the product DOES NOT exist: An If node checks if the missing product's category matches a predefined type (optional filtering). If it passes the filter, a second BrowserAct workflow scrapes detailed product attributes from a dedicated product page (e.g., DigiKey). An AI Agent (Gemini) transforms these attributes into a specific, styled HTML table for the product description. Finally, the product is created in WooCommerce with all scraped details and the AI-generated description. Error Handling:* Multiple *Slack** nodes are configured to alert your team immediately if any scraping task fails or if the product update/creation process encounters an issue. Note: This workflow does not support image uploads for new products. To enable this functionality, you must modify both the n8n and BrowserAct workflows. Requirements BrowserAct** API account for web scraping BrowserAct** n8n Community Node -> (n8n Nodes BrowserAct) BrowserAct* templates named *“WooCommerce Inventory & Stock Synchronization”* and *“WooCommerce Product Data Reconciliation”** Google Sheets** credentials for the supplier list WooCommerce** credentials for product management Google Gemini** account for the AI Agent Slack** credentials for error alerts Need Help? How to Find Your BrowseAct API Key & Workflow ID How to Connect n8n to Browseract How to Use & Customize BrowserAct Templates How to Use the BrowserAct N8N Community Node Workflow Guidance and Showcase STOP Overselling! Auto-Sync WooCommerce Inventory from ANY Supplier