Workflow Templates

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Who is this for? This workflow is designed for anyone who wants to automate AI-driven chat responses integrated with Google Docs and Google Sheets, using the Google Gemini (PaLM) language model via n8n. It’s perfect for teams looking to: Automatically generate AI replies to chat messages, Pull content dynamically from Google Docs, What this Workflow Does Receives chat messages via a webhook trigger. Sends the chat input to the Google Gemini AI Chat Model for generating replies. Optionally retrieves a document from Google Docs if a URL or ID is provided. Uses an AI agent node to coordinate between the AI model and tools like Google Docs. Key Features Integration with Google Gemini (PaLM) AI for natural language understanding and response generation. Ability to fetch and use data from Google Docs dynamically. Modular structure using n8n nodes for flexibility and easy customization. Credential management for Google APIs (Docs, Gemini) via n8n’s built-in credential system. Get Your Google AI API Key Visit Google AI Studio. Click "Create API key in new project". Copy the API key that appears. Add Your Credential in n8n On the workflow canvas, go to the Connect your model (Google Gemini) node. Click the Credential dropdown and select + Create New Credential. Paste your API key into the API Key field. Click Save. Start Chatting! Go to the Example Chat node. Click the "Open Chat" button in its parameter panel. Try asking it one of the example questions: "What's your name?" "What time now in bangladesh?" "What's the weather in bangladesh?" You're now ready to chat with your personal AI agent powered by Google Gemini! 🎉 Requirements n8n instance with internet access. Google Cloud account with: Access to PaLM API (Google Gemini). Proper OAuth2 credentials configured in n8n for Google APIs. 🙋 For Help & Community 👾 Discord: n8n channel 🌐 Website: devcodejourney.com 🔗 LinkedIn: Connect with Shakil 📱 WhatsApp Channel: Join Now 💬 Direct Chat: Message Now

Sora 2 Video Generation: Prompt-to-Video Automation with OpenAI API Who’s it for This template is ideal for content creators, marketers, developers, or anyone needing automated AI video creation from text prompts. Perfect for bulk generation, marketing assets, or rapid prototyping using OpenAI's Sora 2 API. Example use cases: E-commerce sellers creating product showcase videos for multiple items without hiring videographers or renting studios Social media managers generating daily content like travel vlogs, lifestyle videos, or brand stories from simple text descriptions Marketing teams producing promotional videos for campaigns, events, or product launches in minutes instead of days How it works / What it does Submit a text prompt using a form or input node. Workflow sends your prompt to the Sora 2 API endpoint to start video generation. It polls the API to check if the video is still processing or completed. When ready, it retrieves the finished video's download link and automatically saves the file. All actions—prompt submission, status checks, and video retrieval—run without manual oversight. How to set up Use your existing OpenAI API key or create a new one at https://platform.openai.com/api-keys Replace Your_API_Key in the following nodes with your OpenAI API key: Sora 2Video, Get Video, Download Video Adjust the Wait node for Video node intervals if needed — video generation typically takes several minutes Enter your video prompt into the Text Prompt trigger form to start the workflow Requirements OpenAI account & OpenAI API key n8n instance (cloud or self-hosted) A form, webhook, or manual trigger for prompt submission How to customize the workflow Connect the prompt input to external forms, bots, or databases. Add post-processing steps like uploading videos to cloud storage or social platforms. Adjust polling intervals for efficient status checking. Limitations and Usage Tips Prompt Clarity: For optimal video generation results, ensure that prompts are clear, concise, and well-structured. Avoid ambiguity and overly complex language to improve AI interpretation. Processing Duration: Video creation may take several minutes depending on prompt complexity and system load. Users should anticipate this delay and design workflows accordingly. Polling Interval Configuration: Adjust polling intervals thoughtfully to balance prompt responsiveness with API rate limits, optimizing both performance and resource usage. API Dependency: This workflow relies on the availability and quota limits of OpenAI’s Sora 2 API. Users should monitor their API usage to avoid interruptions and service constraints.

Extract and Convert PDF Documents to Markdown with LlamaIndex Cloud API Overview This workflow automatically converts PDF documents to Markdown format using the LlamaIndex Cloud API. LlamaIndex is a powerful data framework that specializes in connecting large language models with external data sources, offering advanced document processing capabilities with high accuracy and intelligent content extraction. How It Works Automatic Processing Pipeline: Form Submission Trigger**: Workflow initiates when a user submits a document through a web form Document Upload**: PDF files are automatically uploaded to LlamaIndex Cloud for processing Smart Status Monitoring**: The system continuously checks processing status and adapts the workflow based on results Conditional Content Extraction**: Upon successful processing, extracted Markdown content is retrieved for further use Setup Instructions Estimated Setup Time: 5-10 minutes Prerequisites LlamaIndex Cloud account and API credentials Access to n8n instance (cloud or self-hosted) Configuration Steps Configure Form Trigger Set up the webhook form trigger with file upload capability Add required fields to capture document metadata and processing preferences Setup LlamaIndex API Connection Obtain your API key from LlamaIndex Cloud dashboard Configure the HTTP Request node with your credentials and endpoint URL Set proper authentication headers and request parameters Configure Status Verification Define polling intervals for status checks (recommended: 10-30 seconds) Set maximum retry attempts to avoid infinite loops Configure success/failure criteria based on API response codes Setup Content Extractor Configure output format preferences (Markdown styling, headers, etc.) Set up error handling for failed extractions Define content storage or forwarding destinations Use Cases Document Digitization**: Convert legacy PDF documents to editable Markdown format Content Management**: Prepare documents for CMS integration or static site generators Knowledge Base Creation**: Transform PDF manuals and guides into searchable Markdown content Academic Research**: Convert research papers and publications for analysis and citation Technical Documentation**: Process PDF specifications and manuals for developer documentation Key Features Fully automated PDF to Markdown conversion Intelligent content structure preservation Error handling and retry mechanisms Status monitoring with real-time feedback Scalable processing for batch operations Requirements LlamaIndex Cloud API key n8n instance (v0.200.0 or higher recommended) Internet connectivity for API access Support For issues related to LlamaIndex API, consult their official documentation docs. For n8n-specific questions, refer to the n8n community forum.

How it works This workflow creates a complete MCPserver that provides comprehensive API integration monitoring and testing capabilities. The server exposes five specialized tools through a single MCP endpoint: API health analysis, webhook reliability testing, rate limit monitoring, authentication verification, and client report generation. External applications can connect to this MCP server to access all monitoring tools. Who is this for This template is designed for DevOps engineers, API developers, integration specialists, and technical teams responsible for maintaining API reliability and performance. It's particularly valuable for organizations managing multiple API integrations, SaaS providers monitoring client integrations, and development teams implementing API monitoring strategies. Requirements MCP Client**: Any MCP-compatible application (Claude Desktop, custom MCP client, or other AI tools) Network Access**: Outbound HTTP/HTTPS access to test API endpoints and webhooks Authentication**: Bearer token authentication for securing the MCP server endpoint Target APIs**: The APIs and webhooks you want to monitor (no special configuration required on target systems) How to set up Configure MCP Server Authentication - Update the MCP Server - API Monitor Entry node with your desired authentication method and generate a secure bearer token for accessing your MCP server Deploy the Workflow - Save and activate the workflow in your n8n instance, noting the MCP server endpoint URL that will be generated for external client connections Connect MCP Client - Configure your MCP client (such as Claude Desktop) to connect to the MCP server endpoint using the authentication token you configured Test Monitoring Tools - Use your MCP client to call the available tools: Analyze Api Health, Validate Webhook Reliability, Monitor API Limits, Verify Authentication, and Generate Client Report with your API endpoints and credentials

🎵 Spotify to MP3 → Upload to Google Drive Automate the process of converting Spotify track URLs into MP3 files, uploading them to Google Drive, and instantly generating shareable links — all triggered by a simple form. ✅ What This Workflow Does Accepts a Spotify URL from a form. Sends the URL to Spotify Downloader MP3 API on RapidAPI. Waits briefly for conversion. Downloads the resulting MP3 file. Uploads it to Google Drive. Sets public sharing permissions for easy access. 🧩 Workflow Structure | Step | Node Name | Description | |------|--------------------------------|-----------------------------------------------------------------------------| | 1 | On form submission | Collects Spotify track URL via an n8n Form Trigger node. | | 2 | Spotify Rapid API | Calls Spotify Downloader MP3 API to generate the MP3 download link. | | 3 | Wait | Ensures download link is processed before proceeding. | | 4 | Downloader | Downloads the MP3 using the generated link. | | 5 | Upload MP3 to Google Drive | Uploads the file using Google Drive credentials. | | 6 | Update Permission | Makes the uploaded file publicly accessible via a shareable link. | 🔧 Requirements n8n instance (self-hosted or cloud) RapidAPI account & subscription to Spotify Downloader MP3 API Google Cloud service account with Drive API access Active Google Drive (root or specified folder) 🚀 How to Use Set up Google API credentials in n8n. Subscribe to the Spotify Downloader MP3 API on RapidAPI. Insert your RapidAPI key into the HTTP Request node. Deploy the workflow and access the webhook form URL. Submit a Spotify URL — the MP3 gets downloaded, uploaded, and shared. 🎯 Use Cases 🎧 Music collectors automating downloads 🧑‍🏫 Teachers creating music-based lessons 🎙 Podcasters pulling music samples 📥 Anyone who needs quick Spotify → MP3 conversion 🛠 Tech Stack n8n**: Visual workflow automation RapidAPI**: Spotify Downloader MP3 API Google Drive**: File storage and sharing Form Trigger**: Input collection interface HTTP Request Node**: Handles API communication 🔐 Notes on Security Do not expose your x-rapidapi-key publicly. Use environment variables or n8n credentials for secure storage. Adjust sharing permissions (reader, writer, or restricted) per your needs. 🔗 API Reference 🎵 Spotify Downloader MP3 API – skdeveloper 📦 Tags spotify mp3 google-drive automation rapidapi n8n music

How it works This workflow synchronizes support tickets in Freshdesk with issues in Linear, enabling smooth collaboration between support and development teams. It triggers on new or updated Freshdesk tickets, maps fields to Linear’s format, and creates linked issues through Linear’s API. Reverse synchronization is also supported, so changes in Linear update the corresponding Freshdesk tickets. Comprehensive logging ensures success and error events are always tracked. Step-by-step 1. Trigger the workflow New Ticket Webhook** – Captures new Freshdesk tickets for issue creation. Update Ticket Webhook** – Detects changes in existing tickets. Linear Issue Updated Webhook** – Listens for updates from Linear. 2. Transform and map data Map Freshdesk Fields to Linear** – Converts priority, status, title, and description for Linear. Map Linear to Freshdesk Fields** – Converts Linear state, priority, and extracts ticket ID for Freshdesk updates. 3. Perform API operations Create Linear Issue** – Sends GraphQL mutation to Linear API. Check Linear Creation Success** – Validates issue creation before linking. Link Freshdesk with Linear ID** – Updates Freshdesk with Linear reference. Update Freshdesk Ticket** – Pushes Linear updates back to Freshdesk. 4. Manage logging and errors Log Linear Creation Success** – Records successful ticket-to-issue sync. Log Linear Creation Error** – Captures and logs issue creation failures. Log Freshdesk Update Success** – Confirms successful reverse sync. Log Missing Ticket ID Error** – Handles missing ticket reference errors. Why use this? Keep support and development teams aligned with real-time updates. Eliminate manual ticket-to-issue handoffs, saving time and reducing errors. Maintain full visibility with detailed success and error logs. Enable bidirectional sync between Freshdesk and Linear for true collaboration. Improve response times by ensuring both teams always work on the latest data.