by Roman Rozenberger
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Who's it for Content creators, marketers, and researchers who need to monitor multiple RSS feeds and get AI-generated summaries without manual work. How it works This workflow automatically monitors RSS feeds, filters new articles from the last X days, checks for duplicates, and generates structured AI summaries. It fetches full article content, converts HTML to markdown, and uses Gemini AI to create consistent summaries with quick takeaways, key points, and practical insights. All data is saved to Google Sheets for easy access and sharing. The system processes RSS feeds in batches, ensuring no duplicate articles are processed twice by checking existing URLs in your Google Sheets. Each new article gets a comprehensive AI summary that includes the main message, key takeaways, important points, and practical applications. Requirements Google Sheets access OpenRouter API key for Gemini AI model or other language model RSS feed URLs to monitor How to set up Copy the template Google Sheet, add your RSS feeds in the "RSS FEEDS" tab, configure Google Sheets and OpenRouter credentials in n8n, and adjust the time filter in the Settings node. The workflow can run manually or on schedule every hour. How to customize Modify AI prompts for different summary styles, change the time filter duration, add more data fields to Google Sheets, or switch to a different AI model in the LLM Chat Model node.
by Ranjan Dailata
The Scrape and Analyze Amazon Product Info with Decodo + OpenAI workflow automates the process of extracting product information from an Amazon product page and transforming it into meaningful insights. The workflow then uses OpenAI to generate descriptive summaries, competitive positioning insights, and structured analytical output based on the extracted information. Disclaimer Please note - This workflow is only available on n8n self-hosted as it’s making use of the community node for the Decodo Web Scraping Who this is for? This workflow is ideal for: E-commerce product researchers Marketplace sellers (Amazon, Flipkart, Shopify, etc.) Competitive intelligence teams Product comparison bloggers and reviewers Pricing and product analytics engineers Automation builders needing AI-powered product insights What problem is this workflow solving? Manually extracting Amazon product details, ads, pricing, reviews, and competitive signals is: Time-consuming Requires switching across tools Difficult to analyze at scale Not structured for reporting Hard to compare products objectively This workflow automates: Web scraping of Amazon product pages Extraction of product features and ad listings AI-generated product summaries Competitive positioning analysis Generation of structured product insight output Export to Google Sheets for tracking and reporting What this workflow does This workflow performs an end-to-end product intelligence pipeline, including: Data Collection Scrapes an Amazon product page using Decodo Retrieves product details and advertisement placements Data Extraction Extracts: Product specs Key feature descriptions Ads data Supplemental metadata AI-Driven Analysis Generates: Descriptive product summary Competitive positioning insights Structured product insight schema Data Consolidation Merges descriptive, analytical, and structured outputs Export & Persistence Aggregates results Writes final dataset to Google Sheets for: tracking comparison reporting product research archives Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n instance** Decodo API credentials** OpenAI API credentials** Make sure to install the Decodo Community Node. Required Credentials Decodo API Go to Credentials Add Decodo API Enter API key Save as: Decodo Credentials account OpenAI API Go to Credentials Select OpenAI Enter API key Save as: OpenAi account Google Sheets Add Google Sheets OAuth Authorize via Google Save as desired account Inputs to configure Modify in Set the Input Fields node: product_url = https://www.amazon.in/Sony-DualSense-Controller-Grey-PlayStation/dp/B0BQXZ11B8 How to customize this workflow to your needs You can easily adapt this workflow for various use cases. Change the product being analyzed Modify: product_url Change AI model In OpenAI nodes: Replace gpt-4.1-mini Use Gemini, Claude, Mistral, Groq (if supported) Customize the insight schema Edit Product Insights node to include: sustainability markers sentiment extraction pricing bands safety compliance brand comparisons Expand data extraction You may extract: product reviews FAQs Q&A seller information delivery and logistics signals Change output destination Replace Google Sheets with: PostgreSQL MySQL Notion Slack Airtable Webhook delivery CSV export Turn it into a batch processor Loop over: multiple ASINs category listings search results pages Summary This workflow provides a complete automated product intelligence engine, combining Decodo’s scraping capabilities with OpenAI’s analytical reasoning to transform Amazon product pages into structured insights, competitive analysis, and summarized evaluations automatically stored for reporting and comparison.
by Miko
The workflow performs tasks that would normally require human intervention on Google News links, transforming the RSS feeds into data that can be used by an automated system like n8n, thus creating a solid foundation for further applications Who is this for? This workflow is ideal for developers, journalists, and content aggregators who need to extract and clean Google News URLs from its RSS feed. What problem does this workflow solve? Google News RSS provides encoded URLs that contain additional tracking parameters. This workflow decodes those URLs and provides clean, direct links to news articles, making them easier to process, share, and analyze. What this workflow does Fetch Google News RSS – Retrieves news articles from Google News based on predefined parameters (language, country). Limit results – Reduces the number of requests to avoid excessive API usage. Extract encoded content – Retrieves the encoded news URLs. Decode the URLs – Uses a decoding mechanism to extract clean links. Remove unwanted characters – Cleans up the decoded URLs to ensure they are properly formatted. Aggregate results – Outputs a final list of clean, readable URLs. Setup Modify RSS parameters (hl, gl) to match your target region. Adjust the result limit to control the number of processed articles. How to customize this workflow To customize this workflow, you can add an HTTP Request node to retrieve the article's text, an HTML Extract node to process the text, an AI node to generate new content, and a WordPress node to publish it Another option is to use an AI Agent node to classify articles by category based on the title or through HTML Extract. You can then save the classified articles using a Google Sheets node, organizing them by category and creating an high quality editorial plan This workflow efficiently processes Google News RSS, removes unnecessary encoding, and delivers clean, shareable URLs. 🚀
by vinci-king-01
How it works Turn Amazon into your personal competitive intelligence goldmine! This AI-powered workflow automatically monitors Amazon markets 24/7, delivering deep competitor insights and pricing intelligence that would take you 10+ hours of manual research weekly. Key Steps Daily Market Scan - Runs automatically at 6:00 AM UTC to capture fresh competitive data AI-Powered Analysis - Uses ScrapeGraphAI to intelligently extract pricing, product details, and market positioning Competitive Intelligence - Analyzes competitor strategies, pricing gaps, and market opportunities Keyword Goldmine - Identifies high-value keyword opportunities your competitors are missing Strategic Insights - Generates actionable recommendations for pricing and positioning Automated Reporting - Delivers comprehensive market reports directly to Google Docs Set up steps Setup time: 15-20 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for intelligent web scraping Set up Google Docs integration - Connect Google OAuth2 for automated report generation Customize Amazon search URL - Target your specific product category or market niche Configure IP rotation - Set up proxy rotation if needed for large-scale monitoring Test with sample products - Start with a small product set to validate data accuracy Set competitive alerts - Define thresholds for price changes and market opportunities Save 10+ hours weekly while staying ahead of your competition with real-time market intelligence!
by Paul
🚀 Google Search Console MCP Server 📋 Description This n8n workflow serves as a Model Context Protocol (MCP) server, connecting MCP-compatible AI tools (like Claude) directly to the Google Search Console APIs. With this workflow, users can automate critical SEO tasks and manage Google Search Console data effortlessly via MCP endpoints. Included Functionalities: 📌 List Verified Sites 📌 Retrieve Detailed Site Information 📌 Access Search Analytics Data 📌 Submit and Manage Sitemaps 📌 Request URL Indexing OAuth2 is fully supported for secure and seamless API interactions. 🛠️ Setup Instructions 🔑 Prerequisites n8n instance** (cloud or self-hosted) Google Cloud project with enabled APIs: Google Search Console API Web Search Indexing API OAuth2 Credentials from Google Cloud ⚙️ Workflow Setup Step 1: Import Workflow Open n8n, select "Import from JSON", and paste this workflow JSON. Step 2: Configure OAuth2 Credentials Navigate to Settings → Credentials. Add new credentials (Google OAuth2 API): Client ID and Client Secret from Google Cloud Scopes: https://www.googleapis.com/auth/webmasters.readonly https://www.googleapis.com/auth/webmasters https://www.googleapis.com/auth/indexing Step 3: Configure Webhooks Webhook URLs auto-generate in MCP Server Trigger node. Ensure webhooks are publicly accessible via HTTPS. Step 4: Testing Test your endpoints with sample HTTP requests to confirm everything is working correctly. 🎯 Usage Examples List Sites**: Fetch all verified Search Console sites. Get Site Info**: Get detailed information about a particular site. Search Analytics**: Pull metrics such as clicks, impressions, and rankings. Submit Sitemap**: Automatically submit sitemaps. Request URL Indexing**: Trigger Google's indexing for specific URLs instantly. 🚩 Use Cases & Applications SEO automation workflows AI-driven SEO analytics Real-time website performance monitoring Automated sitemap management
by Jean-Marie Rizkallah
🧩 Jamf Policies Export to Slack Quickly export and review your entire Jamf policy configuration—including triggers, frequencies, and scope—directly in Slack. This enables IT and security teams to audit policy setups without logging into Jamf or generating reports manually. ❗The Problem Jamf Pro lacks a straightforward way to quickly review or share a list of all configured policies, including key attributes like frequency, scope, or triggers. Security teams often need this for audit or compliance reviews, but navigating Jamf’s UI or exporting via the API is time-consuming. 🔧 This Fixes It This workflow fetches all policies, extracts the most relevant fields, compiles them into a csv file, and posts that readble file into a designated Slack channel—automatically or on demand. ✅ Prerequisites • A Jamf Pro API key (OAuth2) with read access to policies • A Slack app with permission to post files into your chosen channel 🔍 How it works • Manually trigger or use the webhook to initiate the flow • Retrieve all policies from Jamf via the XML API • Convert the XML response into JSON • Split and loop through each policy ID • Retrieve detailed data for each policy • Format relevant fields (ID, name, trigger, scope, etc.) • Convert the final data set into an .csv file • Upload the file to your Slack channel ⚙️ Set up steps • Takes ~10 minutes to configure • Set the Jamf BaseURL in the “Jamf Server” node • Configure Jamf OAuth2 credentials in the HTTP Request nodes • Adjust the fields for export in the “Set-fields” node • Set your Slack credentials and target channel in the “Post to Slack” node • Optional: Customize the exported fields or filename 🔄 Automation Ready Schedule this flow daily/weekly, or tie it to change events to keep your team informed.
by David Ashby
Complete MCP server exposing all AWS Transcribe Tool operations to AI agents. Zero configuration needed - all 4 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 AWS Transcribe Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n AWS Transcribe Tool tool with full error handling 📋 Available Operations (4 total) Every possible AWS Transcribe Tool operation is included: 🔧 Transcriptionjob (4 operations) • Create a transcription job • Delete a transcription job • Get a transcription job • Get many transcription jobs 🤖 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 AWS Transcribe 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 AWS Transcribe 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 HoangSP
Name: AI-Powered Research Agent using Perplexity Sonar Description: This workflow acts as an AI-powered research assistant using the Perplexity Sonar model. When triggered by another workflow, it sends a user-defined prompt to the Perplexity API to retrieve up-to-date search results. The response is then parsed into a clean format for downstream processing. How it Works: Trigger: Activated from another workflow via Execute Workflow Trigger. Prompt Setup: Sets a system role message and user query dynamically. API Call: Sends a POST request to Perplexity's /chat/completions endpoint with your credentials. Response Handling: Extracts the message content from the API response. Output: Returns the result, ready for display or further processing. Requirements: A Perplexity AI API Key Set up authentication via Header Auth with Bearer token Ensure your account allows outbound HTTP requests in n8n Customization Tips: Modify the system prompt to suit your research domain Chain this workflow with other automation like blog creation, summaries, etc. Replace the output handling logic to fit into Google Sheets, Notion, or Telegram
by Jan Willem Altink
This workflow provides a secure API endpoint to remotely trigger other n8n workflows with custom data and to retrieve information about your existing workflows. It's perfect for users who want to integrate n8n into external systems or programmatically manage their automations. example usage: I use this workflow in a Raycast extension i have build, to execute n8n workflows from within Raycast: see Github ++How it works++ Receives API Calls: A webhook listens for incoming HTTP requests (e.g., POST to trigger, GET to retrieve info). Triggers Workflows: If the request is to trigger a workflow, it dynamically identifies the target workflow ID (from query parameters) and any input data (from the request body), then executes that workflow. This means you can control any of your workflows without modifying this manager template. Retrieves Workflow Info: Similarly, if the request is to get information, it dynamically uses query parameters (workflowId, mode, includedWorkflows) to fetch details about one or more n8n workflows (e.g., specific, all, active, inactive; full or summarized data). Responds: Sends back a JSON response indicating success/failure or the requested workflow data. ++Set it up++ Configure Webhook Security: Set up "Header Auth" credentials for the main Webhook node. This is the API key your external services will use. Add n8n API Credentials: For the nodes that fetch workflow information (like "Get specific workflowid", "get all active workflows", etc.), connect your n8n API credentials. This allows the workflow to query your n8n instance. Note Your Webhook URL: Once active, n8n provides a production URL for the webhook (path: workflow-manager). Use this URL to make API calls. Understand API Parameters: To trigger: Use ?workflowId=[ID_OF_WORKFLOW_TO_RUN] and send JSON data in the request body. To get info: Use parameters like ?workflowId=[ID], ?includedWorkflows=[all/active/inactive], and ?mode=[full/summary].
by David Ashby
Complete MCP server exposing all Marketstack Tool operations to AI agents. Zero configuration needed - all 3 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 Marketstack Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Marketstack Tool tool with full error handling 📋 Available Operations (3 total) Every possible Marketstack Tool operation is included: 🔧 Endofdaydata (1 operations) • Get many EoD data 🔧 Exchange (1 operations) • Get an exchange 🔧 Ticker (1 operations) • Get a ticker 🤖 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 Marketstack 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 Marketstack 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
🛠️ seven Tool MCP Server Complete MCP server exposing all seven Tool operations to AI agents. Zero configuration needed - all 2 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 seven Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n seven Tool tool with full error handling 📋 Available Operations (2 total) Every possible seven Tool operation is included: 🔧 Sms (1 operations) • Send an SMS 🔧 Voice (1 operations) • Convert text to voice 🤖 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 seven 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 seven 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 2 topupsapi 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 topupsapi 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 topupsapi 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://polls.apiblueprint.org • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Questions (2 endpoints) • GET /questions: Create Question 1 • POST /questions: Create a New Question 🤖 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 topupsapi 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.