Workflow Templates

💬Communication & Collaboration

Description This workflow automatically monitors online forums for specific keywords, topics, or competitor mentions. It helps you stay on top of relevant discussions without manually checking multiple forums throughout the day. Overview This workflow automatically monitors selected forums for new posts, keywords, or competitor activity. It uses Bright Data to scrape forum content and can notify you or save results to a spreadsheet or other service. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping forum content without getting blocked. (Optional) Google Sheets/Discord/Telegram:** For notifications or data storage. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Notifications (Optional): Configure notification/storage nodes as needed. Customize: Specify the forums and keywords to monitor. Use Cases Brand Monitoring:** Stay updated on mentions of your brand or product. Competitor Tracking:** Monitor competitor activity in your industry forums. Community Managers:** Get alerts for new threads or topics. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #forums #brightdata #webscraping #monitoring #forummonitoring #brandmentions #competitortracking #keywordtracking #n8nworkflow #workflow #nocode #communitymanagement #onlineforums #discussionboards #brandawareness #marketresearch #socialmediamonitoring #contentmonitoring #reputationmanagement #digitalmarketing #businessintelligence #onlinediscussions #competitoranalysis

6 nodes96 views

Validate API Requests with Bearer Token Authentication and Airtable

by Nazmy

Bearer Token Validation This n8n template helps you manage and validate tokens easily using: n8n as your backend workflow engine Airtable as your lightweight token store 🚀 What It Does Stores user tokens securely in Airtable with expiry or usage metadata. Validates incoming tokens in your workflows (e.g., webhook APIs). Rejects invalid or expired tokens automatically for security. Can be extended to generate, rotate, or revoke tokens for user management. How It Works Webhook node receives requests with a Bearer header. Airtable Query looks up the provided token. Validation Logic (Code node): Checks if the token exists. Verifies expiry or usage limits if configured. Returns success if valid, or error if error with describing the issue. Note: This is the simplest way to do auth, just for simplification Why Use This No need for a full backend to manage secure token validation. Clean, modular, and ready for your SaaS workflows. Enjoy building secure automations with n8n + Airtable! 🚀 Built by: Nazmy

WordPress Blog to Google Sheets Sync (Posts, Categories, Tags, Media)

by Grigory Frolov

WordPress Blog to Google Sheets Sync Posts • Categories • Tags • Media 🧩 Overview This n8n workflow automatically syncs your WordPress website content — including posts, categories, tags, and media — into Google Sheets. It helps automate content reporting, SEO analysis, and data backups. The workflow can run on schedule or on demand via a webhook. 💡 Use cases Maintain a live database of blog posts in Google Sheets. Create dashboards in Google Data Studio or Looker Studio. Track new articles for newsletters or social media scheduling. Backup all WordPress content and media outside of your CMS. ⚙️ Prerequisites Before importing the workflow, ensure you have: A WordPress website with the REST API enabled (default in WP 4.7+). Authentication: either Application Passwords or Basic Auth credentials. A Google Sheet with the following tabs: Posts Categories Tags Media The following credentials configured in n8n: HTTP Basic Auth (for WordPress) Google Sheets OAuth2 🚀 Setup instructions Import the workflow into your n8n instance. Replace all example WordPress API URLs with your domain, for example: https://yourdomain.com/wp-json/wp/v2/ Connect your HTTP Basic Auth credentials (WordPress username + Application Password). Connect your Google Sheets OAuth2 account. Update the spreadsheet ID in each Google Sheets node with your own. Adjust the Schedule Trigger (e.g. run daily at 2:00 AM). Run once manually to verify data sync. 🧠 Workflow structure | Section | Description | |----------|--------------| | Schedule / Webhook Trigger | Starts the workflow manually or automatically | | Variables & Loop Vars | Initialize pagination for REST API requests | | Get Posts → Split Out → Update Posts | Fetch and update all WordPress posts | | Get Categories → Update Categories | Sync WordPress categories | | Get Tags → Update Tags | Sync WordPress tags | | Get Media → Split Out → Update Media | Sync media library (images, videos, etc.) | | IF Loops | Handles pagination logic until all items are retrieved | ⚠️ Notes & Limitations Works with standard WordPress REST API endpoints only. Custom post types require editing endpoint URLs. The per_page value defaults to 10; increase for faster syncs. For large sites, consider increasing n8n memory or adding execution logs. Avoid running the workflow too frequently to prevent API rate limits. 🎥 Video Tutorial A step-by-step setup guide is available here: 👉 https://www.youtube.com/watch?v=czSMWyD6f-0 Please subscribe to my YouTube channel to support me: 👉 https://www.youtube.com/@gregfrolovpersonal 👨‍💻 Author Created by: Grigory Frolov SEO & Automation Specialist — helping businesses integrate WordPress, AI, and data tools with n8n. 🧾 License This workflow is provided under the MIT License. Feel free to use, modify, and share improvements with the community.

Real-time Crypto Market Analysis with GPT-4o-mini and CoinMarketCap APIs via Telegram

by Markhah

Overview This n8n workflow is a modular AI analyst system that provides real-time insights from CoinMarketCap’s centralized and decentralized data sources. Using GPT-based AI, the system interprets natural language questions about the crypto market and delegates them to specialized agent workflows. It supports Telegram chat input and returns structured results such as coin quotes, DEX liquidity, exchange info, and community sentiment—all integrated from the CoinMarketCap API ecosystem. Prerequisites a. OpenAI or Gemini account (via GPT-4o-mini or equivalent LLM). b. Telegram Bot API token (for message input/output). c. Valid CoinMarketCap API key. 📦 Required subflows: CoinMarketCap_Crypto_Agent_Tool CoinMarketCap_Exchange_and_Community_Agent_Tool CoinMarketCap_DEXScan_Agent_Tool d. All tools must be installed and configured before use. Each one acts as a specialized endpoint wrapper for CoinMarketCap APIs. How It Works Telegram Input Users send a query to the bot (e.g. “Top DEX pairs on Ethereum”). Session Memory & Agent Brain Session is tracked via chat.id GPT-4o-mini interprets the query, routes to sub-agents Sub-Agent Workflows Crypto Agent: prices, rankings, conversions Exchange Agent: community sentiment, exchange token holdings DEX Agent: OHLCV data, liquidity pools, trades Multi-Agent Coordination AI can combine queries across tools (e.g., get token ID → fetch quote → analyze liquidity) Ensures valid parameters and avoids API errors Telegram Output Final analysis is sent back to the user as a formatted message. Troubleshooting Tips Error Code Meaning Fix 400 Bad request Check symbol/slug/ID validity 401 Unauthorized Verify CoinMarketCap API key 429 Rate limit exceeded Throttle or upgrade API tier 500 Server error Retry with backoff or report to CMC Example Telegram Queries “Show me top 5 coins by market cap” “Get price of ETH on Uniswap and Binance” “How much liquidity is in SOL-USDC pair?” “Fear & Greed Index and trending tokens” SEO Tags (ẩn hoặc ghi chú riêng): coinmarketcap, n8n crypto analyst, crypto ai telegram bot, dex liquidity, CMC price tracker, gpt-4o crypto market, token sentiment dashboard, fear and greed index

🤖AI & Machine Learning

6 nodes1 views

Beginner AI Dataset Generator using OpenAI + LangChain in n8n

by Robert Breen

This n8n workflow dynamically generates a realistic sample dataset based on a single topic you provide. It uses OpenAI (via LangChain) and n8n’s built-in nodes to: Generate structured JSON data for 5 columns with 3–5 values each Flatten that data into a single text blob Infer meaningful column names via a second AI call Pivot, split, merge, and rename columns automatically Output a clean, labeled dataset ready for export or further processing ⚙️ Prerequisites OpenAI API Key Visit: https://platform.openai.com/account/api-keys Create a new key In n8n: Credentials → New → OpenAI API, paste key, name it “OpenAi account” LangChain nodes enabled in your n8n instance 🥇 Step 1: Set Up OpenAI Credential Go to OpenAI API Keys Create and copy your key In n8n: Credentials → New → OpenAI API → paste key as “OpenAi account” 🥈 Step 2: Manual Trigger Add Manual Trigger to start the workflow 🥉 Step 3: Set Topic Add a Set node named Set Topic to Search Field: Topic = n8n use cases (or any topic you choose) ✨ Step 4: Generate Structured Data LangChain Agent** node Generate Random Data Connect to OpenAI Chat Model1 and Tool: Inject Creativity1 System prompt: instruct AI to output 5 columns of realistic values in JSON 🔧 Step 5: Parse AI Output Structured Output Parser** to validate JSON 🔄 Step 6: Flatten Data Code** node Outpt all Data to One Field Joins all values into a comma-separated string for column naming 🧠 Step 7: Generate Column Names LangChain Agent** Generate Column Names Connect to OpenAI Chat Model2 Prompt: infer 5 column names from the string 🔢 Step 8: Pivot Names Row Code** node Pivot Column Names transforms array into { column1: name1, … } 🪓 Step 9: Split Columns 5 SplitOut nodes to break each array back into rows per column 🔗 Step 10: Merge Rows Merge** node Merge Columns together using combineByPosition 🏷️ Step 11: Rename Columns Set** node Rename Columns assigns the AI-generated names to each column 🔗 Step 12: Final Output Merge** Append Column Names combines data and header row 🏁 Done! You now have a fully AI-driven, labeled dataset generated from a single topic—no external services needed. Easily extend by adding a Google Sheets or HTTP node to export. 📬 Need Help or Want to Customize This? 📧 robert@ynteractive.com 🔗 LinkedIn

OpenAI examples: ChatGPT, DALLE-2, Whisper-1 – 5-in-1

by Eduard

Primer workflow for OpenAI models: ChatGPT, DALLE-2, Whisper This workflow contains 5 examples on how to work with OpenAI API. Transcribe voice into text via Whisper model (disabled, please put your own mp3 file with voice) The old way of using OpenAI conversational model via text-davinci-003 Examples 1.x. Simple ChatGPT calls. Text completion and text edit Example 2. Provide system and user content into ChatGPT Examples 3.x. Create system / user / assistanc content via Code Node. Promtp chaining technique example Example 4. Generate code via ChatGPT Example 5. Return multiple answers. Useful for providing picking the most relevant reply IMPORTANT! Do not run the whole workflow, it's rather slow Better execute the last node of each branch or simply disconnect branches that are not needed

🤖AI & Machine Learning

4 nodes25181 views

Smartlead Email Campaign Analytics Dashboard with Google Sheets Integration

by Rahi

Workflow 1: Domain and Email Health 🩺 This part of the workflow is triggered every 5 hours by the Schedule Trigger1 node. Its purpose is to pull health metrics for both email domains and individual email addresses. How it Works: ++Schedule Trigger:++ The Schedule Trigger1 node initiates the workflow every 5 hours. ++API Requests:++ Two separate HTTP Request nodes, HTTP Request5 and HTTP Request6, make API calls to Smartlead. ++HTTP Request5 calls++ the endpoint for domain-wise health metrics. ++HTTP Request6 calls++ the endpoint for email-wise health metrics. Both requests use the same api_key and a date range from 2025-07-04 to the current day. ++Data Splitting:++ The Split Out5 and Split Out6 nodes take the JSON response from the API calls and split the data into individual items. This is necessary so each row of data can be processed and added to Google Sheets separately. ++Google Sheets Integration:++ Finally, the Append or update row in sheet5 and Append or update row in sheet6 nodes update two different Google Sheets: ++Append or update row in sheet5 adds++ or updates rows in the DomainHealth sheet, matching on the domain column. ++Append or update row in sheet6 adds++ or updates rows in the EmailHealth sheet, matching on the from_email column. Workflow 2: Global and Campaign-Specific Analytics 📊 This second part of the workflow is triggered every 2 hours by the Schedule Trigger node. Its goal is to get a day-by-day overview of email engagement and campaign-specific performance. How it Works: Schedule Trigger: The Schedule Trigger node starts this workflow every 2 hours. ++API Requests:++ Two HTTP Request nodes, HTTP Request and HTTP Request1, call different Smartlead API endpoints. ++HTTP Request++ retrieves day-wise overall stats for email engagement. ++HTTP Request1 ++retrieves overall stats for each campaign. ++Data Splitting:++ The Split Out and Split Out1 nodes separate the JSON responses into individual data items for processing. ++Google Sheets Integration:++ The Append or update row in sheet and Append or update row in sheet1 nodes then write the data to Google Sheets. ++Append or update row in sheet++ updates the Sheet1 sheet with day-wise metrics, using the date as a matching column. ++Append or update row in sheet1++ updates the CampaignWise sheet with campaign performance metrics, using the campaign id to match rows.

Extract & Transform HackerNews Data to Google Docs using Gemini 2.0 Flash

by Ranjan Dailata

💬Communication & Collaboration

Description This workflow automates the process of scraping the latest discussions from HackerNews, transforming raw threads into human readable content using Google Gemini, and exporting the final content into a well-formatted Google Doc. Overview This n8n workflow is responsible for extracting trending posts from the HackerNews API. It loops through each item, performs HTTP data extraction, utilizes Google Gemini to generate human-readable insights, and then exports the enriched content into Google Docs for distribution, archiving, or content creation. Who this workflow is for Tech Newsletter Writers**: Automate the collection and summarization of trending HackerNews posts for inclusion in weekly or daily newsletters. Content Creators & Bloggers**: Quickly generate structured summaries and insights from HackerNews threads to use as inspiration or supporting content for blog posts, videos, or social media. Startup Founders & Product Builders**: Monitor HackerNews for discussions relevant to your niche or competitors, and keep a pulse on the community’s opinions. Investors & Analysts**: Surface early signals from the tech ecosystem by identifying what’s trending and how the community is reacting. Researchers & Students**: Analyze popular discussions and emerging trends in technology, programming, and startups—enriched with AI-generated insights. Digital Agencies & Consultants**: Offer HackerNews monitoring and insight reports as a value-added service to clients interested in the tech space. Tools Used n8n**: The core automation engine that manages the trigger, transformation, and export. HackerNews API**: Provides access to trending or new HN posts. Google Gemini**: Enriches HackerNews content with structured insights and human-like summaries. Google Docs**: Automatically creates and updates a document with the enriched content, ready for sharing or publishing. How to Install Import the Workflow**: Download the .json file and import it into your n8n instance. Set Up HackerNews Source**: Choose whether to use the HN API (via HTTP Request node) or RSS Feed node. Configure Gemini API**: Add your Google Gemini API key and design the prompt to extract pros/cons, key themes, or insights. Set Up Google Docs Integration**: Connect your Google account and configure the Google Docs node to create/update a document. Test and Deploy**: Run a test job to ensure data flows correctly and outputs are formatted as expected. Use Cases Tech Newsletter Authors**: Generate ready-to-use summaries of trending HackerNews threads. Startup Founders**: Stay informed on key discussions, product launches, and community feedback. Investors & Analysts**: Spot early trends, technical insights, and startup momentum directly from HN. Researchers**: Track community reactions to new technologies or frameworks. Content Creators**: Use the enriched data to spark blog posts, YouTube scripts, or LinkedIn updates. Connect with Me Email: ranjancse@gmail.com LinkedIn: https://www.linkedin.com/in/ranjan-dailata/ Get Bright Data: Bright Data (Supports free workflows with a small commission) #n8n #automation #hackernews #contentcuration #aiwriting #geminiapi #googlegemini #techtrends #newsletterautomation #googleworkspace #rssautomation #nocode #structureddata #webscraping #contentautomation #hninsights #aiworkflow #googleintegration #webmonitoring #hnnews #aiassistant #gdocs #automationtools #gptlike #geminiwriter

5 nodes3117 views

Monitor G2 competitors reviews [Google Sheets, ScrapingBee, Slack]

by Lucas Perret

This workflow monitor G2 reviews URLS. When a new review is published, it will: trigger a Slack notification record the review in Google Sheets To install it, you'll need: access to Slack, Google Sheets and ScrapingBee Full guide here: https://lempire.notion.site/Scrape-G2-reviews-with-n8n-3f46e280e8f24a68b3797f98d2fba433?pvs=4

Adaptive RAG Strategy with Query Classification & Retrieval (Gemini & Qdrant)

by dmr

This n8n workflow implements a version of the Adaptive Retrieval-Augmented Generation (RAG) framework. It recognizes that the best way to retrieve information often depends on the type of question asked. Instead of a one-size-fits-all approach, this workflow adapts its strategy based on the user's query intent. 🌟 How it Works Receive Query: Takes a user query as input (along with context like a chat session ID and Vector Store collection ID if used as sub-workflow). Classify Query: First, the workflow classifies the query into a predefined category. This template uses four examples: Factual: For specific facts. Analytical: For deeper explanations or comparisons. Opinion: For subjective viewpoints. Contextual: For questions relying on specific background. Select & Adapt Strategy: Based on the classification, it selects a corresponding strategy to prepare for information retrieval. The example strategies aim to: Factual: Refine the query for precision. Analytical: Break the query into sub-questions for broad coverage. Opinion: Identify different viewpoints to look for. Contextual: Incorporate implied or user-specific context. Retrieve Info: Uses the output of the selected strategy to search the specified knowledge base (Qdrant vector store - change as needed) for relevant documents. Generate Response: Constructs a response using the retrieved documents, guided by a prompt tailored to the original query type. By adapting the retrieval strategy, this workflow aims to provide more relevant results tailored to the user's intent. ⚙️ Usage & Flexibility Sub-Workflow:** Designed to be called from other n8n workflows, passing user_query, chat_memory_key, and vector_store_id as inputs. Chat Testing:** Can also be triggered directly via the n8n Chat interface for easy testing and interaction. Customizable Framework:** The query categories (Factual, Analytical, etc.) and the associated retrieval strategies are examples. You can modify or replace them entirely to fit your specific domain or requirements. 🛠️ Requirements Credentials:** You will need API credentials configured in your n8n instance for: Google Gemini (AI Models) Qdrant (Vector Store)

Create Viral Social Media Videos with FalAI Flux/Kling and GPT-4 Automation

by Matthew