Insert a document in MongoDB
Companion workflow for MongoDB node docs
By amudhanOpenAI-powered tweet generator
This workflow uses OpenAI to generate tweets to be stored in Airtable for review. A JS snippet handles the topics to be tweeted about in the form of hashtags.
By Gareth RollEvaluation metric example: RAG document relevance
AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: retrieved document relevance (i.e. whether the information retrieved from a vector store is relevant to the question). The workflow takes a question and checks whether the information retrieved to answer it is relevant. To run this workflow, you need to insert documents into a vector data store, so that they can be retrieved by the agent to answer questions. You can do this by running the top part of the workflow once. The main workflow works as follows: We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info We make sure that the agent outputs the list data from the tools that it used If we’re evaluating (i.e. the execution started from the evaluation trigger), we calculate the relevance metric using AI to compare the retrieved documents with the question We pass this information back to n8n as a metric If we’re not evaluating we avoid calculating the metric, to reduce cost
By David RobertsAutomated local business lead generator with AI, social media & WhatsApp links
Automated Local Business Lead Generator with AI, Social Media & WhatsApp Links This workflow automates the process of generating and managing local business leads by scraping Google Maps data, analyzing business information with AI, and creating personalized outreach messages. The system searches for local businesses based on keywords and locations, extracts their contact information and reviews, then generates professional outreach messages tailored to each business. Results are stored in Google Sheets and notifications are sent via Telegram. 📊 Google Sheets Template Use this template: Local Business Lead Generator 🔑 Key Features 🔍 Searches Google Maps for local businesses using SerpAPI based on keywords and location parameters 📋 Collects comprehensive business information including name, address, rating, reviews, phone numbers, and websites 🤖 Uses OpenRouter's LLM to analyze business data and generate personalized outreach messages 🌐 Analyzes business websites to provide targeted improvement suggestions 📱 Automatically detects Instagram and TikTok profiles from business websites 🗣️ Generates messages in the local language based on country code settings 📊 Organizes and stores all collected data in Google Sheets with proper categorization 🚀 Sends real-time updates and lead summaries via Telegram bot 💬 Automatically creates WhatsApp links for easy business communication --- 🔧 Requirements SerpAPI Account + API Key – For Google Maps business data extraction OpenRouter Account + API Key – For AI-powered message generation and analysis Telegram Bot + API Token – For notifications and bot interactions Google Sheets – Connected to n8n for data storage Google Sheets Template – Pre-configured with proper column structure --- 🎁 Benefits Fully automated lead generation and outreach system Saves time and increases efficiency for local business marketing High personalization improves engagement and response rate Scalable for any niche or location
By Budi SJGet all contacts of HubSpot account
No description available.
By sshaligrCompare sequential, agent-based, and parallel LLM processing with Claude 3.7
This workflow demonstrates three distinct approaches to chaining LLM operations using Claude 3.7 Sonnet. Connect to any section to experience the differences in implementation, performance, and capabilities. What you'll find: 1️⃣ Naive Sequential Chaining The simplest but least efficient approach - connecting LLM nodes in a direct sequence. Easy to set up for beginners but becomes unwieldy and slow as your chain grows. 2️⃣ Agent-Based Processing with Memory Process a list of instructions through a single AI Agent that maintains conversation history. This structured approach provides better context management while keeping your workflow organized. 3️⃣ Parallel Processing for Maximum Speed Split your prompts and process them simultaneously for much faster results. Ideal when you need to run multiple independent tasks without shared context. Setup Instructions: API Credentials: Configure your Anthropic API key in the credentials manager. This workflow uses Claude 3.7 Sonnet, but you can modify the model in each Anthropic Chat Model node, or pick an entirely different LLM. For Cloud Users: If using the parallel processing method (section 3), replace {{ $env.WEBHOOK_URL }} in the "LLM steps - parallel" HTTP Request node with your n8n instance URL. Test Data: The workflow fetches content from the n8n blog by default. You can modify this part to use a different content or a data source. Customization: Each section contains a set of example prompts. Modify the "Initial prompts" nodes to change the questions asked to the LLM. Compare these methods to understand the trade-offs between simplicity, speed, and context management in your AI workflows! --- Follow me on LinkedIn for more tips on AI automation and n8n workflows!
By EduardAutomated email blast with follow-ups & response tracking
This n8n workflow automates email blasts with follow-ups and response tracking by reading contact data from a Google Sheet daily, looping through contacts to send personalized emails based on follow-up stages via Gmail, updating the sheet with status changes, and monitoring replies for logging. Why Use It This workflow streamlines email marketing campaigns by automating personalized email distribution, managing follow-up sequences, and tracking responses without manual intervention, saving time, improving engagement, and providing actionable insights into contact interactions. How to Import It Download the Workflow JSON: Obtain the workflow file from the n8n template or create it based on this document. Import into n8n: In your n8n instance, go to "Workflows," click the three dots, select "Import from File," and upload the JSON. Configure Credentials: Set up Gmail and Google Sheets credentials in n8n. Run the Workflow: Activate the scheduled trigger and test with a sample Google Sheet. System Architecture Email Blast Pipeline: Daily Trigger - 9 AM: Initiates the workflow daily at 9 AM via Cron. Read Contact Data from Google Sheet: Fetches contact details from the sheet. Loop Through Contacts: Processes each contact individually. Determine Follow-Up Stage: Identifies the current stage for each contact. Send Main/Follow-Up Email: Delivers the appropriate email via Gmail. Update Sheet Status: Updates the Google Sheet with the latest status. Response Tracking Flow: Check Gmail for Replies: Monitors Gmail for email responses. Log Responses: Records responses in the Google Sheet. Google Sheet File Structure Sheet Name: EmailCampaign Range: A1:F10 (or adjust based on needs) | A | B | C | D | E | F | |------------|------------|---------------|---------------|---------------|---------------| | name | email | stage | lastemaildate | status | response | | John Doe | john@example.com | Initial | 2025-08-07 | Pending | | | Jane Smith | jane@example.com | Follow-Up 1 | 2025-08-06 | Sent | "Interested" | | Bob Jones | bob@example.com | Follow-Up 2 | 2025-08-05 | Replied | "Follow up later" | Columns: name: Contact’s full name. email: Contact’s email address for sending emails. stage: Current follow-up stage (e.g., Initial, Follow-Up 1, Follow-Up 2). lastemaildate: Date of the last email sent. status: Current status (e.g., Pending, Sent, Replied). response: Logged response from the contact (updated after reply detection). Customization Ideas Adjust Schedule: Change the Cron trigger to hourly or weekly based on campaign needs. Add Email Templates: Customize email content for different stages or audiences. Incorporate SMS: Add WhatsApp or SMS follow-ups using additional nodes. Enhance Tracking: Integrate a dashboard (e.g., Google Data Studio) for real-time campaign analytics. Automate Segmentation: Add logic to segment contacts by industry or interest for targeted emails. Requirements to Run This Workflow Google Sheets Account: For storing and managing contact data and responses. Gmail Account: For sending emails and checking replies (requires IMAP enabled). n8n Instance: With Google Sheets and Gmail connectors configured. Cron Service: For scheduling the daily trigger. Internet Connection: To access Google Sheets and Gmail APIs. API Credentials: Gmail OAuth2 and Google Sheets API credentials set up in n8n. --- Notes Ensure the Google Sheet is shared with the n8n service account or has appropriate permissions. Test the workflow with a small contact list to verify email delivery and response logging. Adjust the stage logic in the "Determine Follow-Up Stage" node to match your campaign structure.
By Oneclick AI SquadOne telegram chat to edit, thumbnail & auto-post your videos everywhere
This workflow turns any Telegram bot into an AI-powered social media command center for photos, videos and voice notes. video demo From one Telegram chat you can: Send a photo and auto-post it to Instagram, TikTok and Pinterest with AI captions. Send a video and: Let AI generate titles + descriptions and upload it to TikTok, Instagram and YouTube. Use /thumb to generate 4 custom thumbnails with Nano Banana Pro. Use /edit ... to run FFmpeg edits (cut, mute, resize, speed, etc.) via Upload-Post FFmpeg jobs and get the edited video back in Telegram. Send a voice note and turn it into posts for LinkedIn, X (Twitter) and Threads, then auto-publish. Keep human approval in the loop: every caption or text post is shown in Telegram for you to accept before publishing. Out of the box, the captions and long descriptions are optimized for Spanish (es-ES), but you can easily change the prompts to any language or brand voice. --- What You Can Do From Telegram Photo → Instagram, TikTok & Pinterest Just send a photo (or image as document) to your Telegram bot: The workflow downloads the photo from Telegram. Gemini 2.5 Flash analyzes the image plus your caption/text (if any). An AI Agent generates platform-specific descriptions for: TikTok (short hook, 90 chars) Instagram Pinterest (title + description) You receive a message in Telegram with all the proposed descriptions. You approve or reject with inline buttons. On approval, Upload-Post publishes the photo to: Instagram TikTok Pinterest (to the board you configured) and sends back a status message with success flags, post URLs and error messages. --- Video → TikTok, Instagram & YouTube (no commands) If you send a video with no special caption: The workflow treats it as a standard video post. It fetches the file from Telegram. Gemini 2.5 Flash analyzes the video and describes its content. An AI Agent turns that description + your caption into: TikTok description Instagram description YouTube title + description You get a Telegram message with the three platform descriptions to review. Once you approve: It shows “Uploading…” in Telegram. The video is sent to Upload-Post, which uploads to TikTok, Instagram and YouTube with the generated text. Finally, you receive an upload report for each platform (success, URL, error message). --- /thumb → AI Thumbnails for Your Video (Nano Banana Pro) If you send a video with caption exactly /thumb: The workflow downloads the video. Gemini 2.5 Flash generates a long, SEO-rich description in Spanish of everything that happens in the video. A second AI Agent uses that detailed description to create 3 concepts: Each concept has: title, description, and a full prompt_thumbnail (Spanish, single line) specially crafted for Nano Banana Pro. In Telegram you see the 3 concepts (titles) and select: 0, 1, 2 or “create new”. Once you choose a concept: The prompt is sent to Nano Banana Pro (fal-ai/nano-banana-pro/edit) with your reference face image (configurable). Nano Banana Pro generates 4 thumbnails (16:9). The workflow downloads the 4 images and sends them back to you in Telegram as photos so you can pick and use your favorite in your YouTube/Upload-Post pipeline. Use /thumb whenever you already have the video and just want killer thumbnails generated with AI. --- /edit … → Natural-Language FFmpeg Video Editor If you send a video with a caption starting with /edit, for example: /edit cut the first 3 seconds and remove the audio /edit crop to vertical 9:16 and speed up x1.5 /edit blur the background and keep the subject centered The workflow behaves as a text-to-FFmpeg command generator: An AI Agent (powered by Gemini) reads your /edit instructions. It generates a safe FFmpeg command in JSON format: Always uses ffmpeg -y Uses {input} and {output} placeholders No semicolons and no dangerous shell characters The workflow then: Downloads the original video from Telegram. Calls Upload-Post FFmpeg jobs API with the video and the generated full_command. Polls the job status until it’s finished. Downloads the processed (edited) video. Sends the edited video back to you in Telegram with a simple sendVideo node. This makes Telegram a front-end for a remote FFmpeg engine: you describe the edit in natural language, and the workflow handles all the FFmpeg complexity. > Note: The edited video is returned to Telegram; if you want to auto-post it, simply send the new video again without /edit so it goes through the normal multi-platform publishing path. --- Voice Notes → LinkedIn, X & Threads (Text Posts) For voice messages: The Telegram Trigger detects message.voice. The workflow downloads the audio file. OpenAI Whisper transcribes the recording. An AI Agent turns the transcription into: A LinkedIn post (Spanish, long-form dev/creator style, based on your examples). A Threads post (Spanish, up to ~500 chars). A Tweet / X post or thread (English, using hooks + hashtags like n8n, automation, dev). In Telegram you see a preview message with the suggested copy for Threads, LinkedIn and X. After you approve: You get an “Uploading…” message. Upload-Post publishes: To your LinkedIn organization page (configured by ID). To X (Twitter). To Threads. The workflow sends a status message with success flags and URLs for each platform. This is perfect for “talk to your phone, ship content to all your text platforms”. --- How the Workflow Is Structured Telegram Trigger Listens to every incoming message and routes by type: /start → No-Op voice → Audio pipeline document/photo → Photo pipeline video → Video/thumbnail/editor pipelines (/thumb, /edit or normal) AI Blocks (Gemini + OpenAI) Gemini 2.5 Flash for: Photo understanding. Short video descriptions (for auto-posting). Long, detailed video summaries (for thumbnail generator). OpenAI Whisper for voice transcription. Multiple AI Agents (Gemini chat) with structured JSON output parsers for: Per-platform social captions. Threads/LinkedIn/X posts. Thumbnail prompts and title concepts. FFmpeg command generation. Upload-Post Integration Photos → Instagram, TikTok, Pinterest. Videos → TikTok, Instagram, YouTube. Text → LinkedIn page, X, Threads. FFmpeg job endpoint for server-side video editing. All uploads return status, URL and error messages back into Telegram. Human-in-the-Loop All critical AI outputs go through sendAndWait nodes in Telegram: You review and choose whether to publish or not. You choose which thumbnail concept to use. --- Requirements & Setup Accounts & APIs Telegram bot (via @BotFather). Upload-Post.com account with your social profiles connected. OpenAI API key (Whisper). Google Gemini API key (AI Studio). Nano Banana Pro / fal.ai key (for thumbnails). Runtime n8n instance (cloud or self-hosted). FFmpeg available where n8n runs (Docker image, VM, etc.) for local checks if needed (the heavy lifting is delegated to Upload-Post FFmpeg jobs). Configuration Create Telegram credentials with your bot token. Create Upload-Post credentials with your API token. Set uploadpostuser and pinterestboardid in the Edit Fields node. Optionally replace: Example face image URL used for Nano Banana Pro. LinkedIn organization ID. Any language / tone in the AI agent system prompts. --- Ideal Use Cases Creators & influencers who want to post to every platform from one Telegram chat. Agencies who want a “content butler” clients can use without touching n8n. Solo devs & makers who publish workflows, devlogs and product updates and want: Multi-platform video posts. Voice → LinkedIn/X/Threads posts. Easy text-based video editing and thumbnail generation. Install this template, plug in your keys, talk to your bot in Telegram, and turn it into your all-in-one AI social media machine.
By Juan Carlos Cavero GraciaInstant Gmail notifications for Google Form submissions
Description Get a single Gmail notification immediately whenever someone submits your Google Forms. The workflow watches the Form-linked Google Sheets for new rows and sends a clean, readable email within about a minute—perfect for time-sensitive workflows. Context Stay responsive to urgent requests without inbox overload. Get notified immediately when new submissions arrive, with all key details in one clean email. Who is this for? Teams collecting support requests, project inputs, or approvals. Anyone who needs to respond quickly to new form submissions. Perfect for time-sensitive workflows. Requirements Google account A Google Forms linked to a Google Sheets (Responses → “Link to Sheet”) Gmail account connected to n8n (OAuth) Steps 🗒️ Use the sticky notes in the n8n canvas to: Create a Google Forms and link it to a Google Sheets. Credentials: Add/verify Google (Sheets) and Gmail credentials in n8n. Add Google Sheets Trigger node. Spreadsheet: your Form-linked sheet. Polling interval: every 1 minute (or adjust as needed). Send Gmail: Add Gmail node and set up recipient team inbox or on-call email. Test & Activate: Submit a sample form, wait 1 minute, confirm the email. Make sure the workflow is always activated You’ll get this: A Gmail message with key details (requester, summary, priority, link to the sheet), easy to scan and act on. Tutorial video Watch the Youtube Tutorial video How it works ⏰ Trigger: workflow runs every time you get a request from the form (trigger checks every minute) 📝 Prepare: Format the submission into a concise message. 📨 Notify: Sends one Gmail email per submission About me : I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin
By Yassin ZeharEbook to audiobook converter using MiniMax and FFmpeg
Ebook to Audiobook Converter [](https://youtu.be/xKqkjXIPZoM) ▶️ Watch Full Demo Video --- What It Does Turn any PDF ebook into a professional audiobook automatically. Upload a PDF, get an MP3 audiobook in your Google Drive. Perfect for listening to books, research papers, or documents on the go. Example: Input PDF → Output Audiobook Key Features Upload PDF via web form → Get MP3 audiobook in Google Drive Natural-sounding AI voices (MiniMax Speech-02-HD) Automatic text extraction, chunking, and audio merging Customizable voice, speed, and emotion settings Processes long books in batches with smart rate limiting Perfect For Students: Turn textbooks into study audiobooks Professionals: Listen to reports and documents while commuting Content Creators: Repurpose written content as audio Accessibility: Make content accessible to visually impaired users Requirements | Component | Details | |-----------|---------| | n8n | Self-hosted ONLY (cannot run on n8n Cloud) | | FFmpeg | Must be installed in your n8n environment | | Replicate API | For MiniMax TTS (Sign up here) | | Google Drive | OAuth2 credentials + "Audiobook" folder | ⚠️ Important: This workflow does NOT work on n8n Cloud because FFmpeg installation is required. Quick Setup Install FFmpeg Docker users: bash docker exec -it <n8n-container-name> /bin/bash apt-get update && apt-get install -y ffmpeg Native installation: bash sudo apt-get install ffmpeg Linux brew install ffmpeg macOS Get API Keys Replicate: Sign up at replicate.com and copy your API token Google Drive: Set up OAuth2 in n8n and create an "Audiobook" folder in Drive Import & Configure Import n8n.json into your n8n instance Replace the Replicate API token in the "MINIMAX TTS" node Configure Google Drive credentials and select your "Audiobook" folder Activate the workflow Cost Estimate | Component | Cost | |-----------|------| | MiniMax TTS API | ~$0.15 per 1000 characters (~$3-5 for average book) | | Google Drive Storage | Free (up to 15GB) | | Processing Time | ~1-2 minutes per 10 pages | How It Works PDF Upload → Extract Text → Split into Chunks → Convert to Speech (batches of 5) → Merge Audio Files (FFmpeg) → Upload to Google Drive The workflow uses four main modules: Extraction: PDF text extraction and intelligent chunking Conversion: MiniMax TTS processes text in batches Merging: FFmpeg combines all audio files seamlessly Upload: Final audiobook saved to Google Drive Voice Settings (Customizable) json { "voiceid": "FriendlyPerson", "emotion": "happy", "speed": 1, "pitch": 0 } Available emotions: happy, neutral, sad, angry, excited Limitations ⚠️ Self-hosted n8n ONLY (not compatible with n8n Cloud) PDF files only (not EPUB, MOBI, or scanned images) Large books (500+ pages) take longer to process Requires FFmpeg installation (see setup above) Troubleshooting FFmpeg not found? Docker: Run docker exec -it <container> /bin/bash then apt-get install ffmpeg Native: Run sudo apt-get install ffmpeg (Linux) or brew install ffmpeg (macOS) Rate limit errors? Increase wait time in the "WAITS FOR 5 SECONDS" node to 10-15 seconds Google Drive upload fails? Make sure you created the "Audiobook" folder in your Google Drive Reconfigure OAuth2 credentials in n8n --- Created by emp0 | More workflows: n8n Gallery
By Jay Emp0🛠️ Google Drive tool MCP server 💪 all 17 operations
Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? Join the community Complete MCP server exposing all Google Drive Tool operations to AI agents. Zero configuration needed - all 17 operations pre-built. ⚡ Quick Setup 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 Google Drive Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Google Drive Tool tool with full error handling 📋 Available Operations (17 total) Every possible Google Drive Tool operation is included: 📄 File (8 operations) • Copy file • Create file from text • Delete a file • Download file • Move file • Share file • Update file • Upload file 🔧 Filefolder (1 operations) • Search files and folders 📁 Folder (3 operations) • Create folder • Delete folder • Share folder 🔧 Drive (5 operations) • Create shared drive • Delete shared drive • Get shared drive • Get many shared drives • Update shared drive 🤖 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 Google Drive 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 Google Drive 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 AshbyAutomate PDF invoice generation & delivery with Gmail and Google Drive storage
How it works Automatically generates professional PDF invoices from webhook data and delivers them via email while storing backups in Google Drive. Perfect for freelancers, small businesses, and service providers who need automated billing workflows. Set up steps Configure environment variables for company information (name, address, email, phone). Set up your PDF generation API service account (PDFShift recommended). Configure SMTP email credentials for invoice delivery. Set up Google Drive OAuth2 for cloud storage. Deploy the workflow and test with sample invoice data. Key features Smart invoice number generation if not provided Automatic tax calculations with configurable rates Professional HTML templates with company branding Parallel processing for email and storage Comprehensive error handling and validation Detailed success confirmation responses Required environment variables COMPANY_NAME - Your business name COMPANY_ADDRESS - Business mailing address COMPANY_EMAIL - Billing contact email COMPANY_PHONE - Business phone number PDFAPIURL - PDF generation service endpoint PDFAPIKEY - API authentication key GDRIVEINVOICEFOLDER_ID - Google Drive folder ID API requirements PDF generation service (PDFShift, HTML/CSS to PDF API, or similar), SMTP email service for delivery, Google Drive API access for storage. Input format json { "customerName": "John Smith", "customerEmail": "john@example.com", "items": [ {"description": "Web Design", "quantity": 1, "price": 500} ], "dueDate": "2025-02-15" }
By Ibrahim Emre POLAT