by Intuz
This n8n template delivers a complete AI-powered solution for automated LinkedIn posts, including unique content, custom images, and optimized hashtags. Use cases are many: Generate and schedule tailored LinkedIn content for different use-cases. By feeding the AI specific prompts, you can create specific post depending upon the topics and visuals to maintain a consistency yet and an online presence. How it works Maintaining a consistent and engaging presence on LinkedIn can be time-consuming, requiring constant ideation, content creation, and manual posting. This workflow takes that burden off your shoulders, delivering a fully automated solution for generating and publishing high-quality LinkedIn content. Scheduled Content Engine: Each day (or on your chosen schedule), the workflow kicks into gear, ensuring a fresh stream of content. Smart Topic & Content Generation: Using the power of Google Gemini, it intelligently crafts unique content topics and then expands them into full, engaging posts, ensuring your message is always fresh and relevant. Dynamic Image Creation: To make your posts stand out, the workflow leverages an AI image generator (like DALL-E) to produce a custom, eye-catching visual that perfectly complements your generated text. SEO-Optimized Hashtag Generation: Google Gemini then analyzes your newly created post and automatically generates a set of relevant, trending, and SEO-friendly hashtags, significantly boosting your content's reach and discoverability. Seamless LinkedIn Publishing: Finally, all these elements—your compelling text, unique image, and powerful hashtags—are merged and automatically published to your LinkedIn profile, establishing you as a thought leader with minimal effort. How to Use: Quick Start Guide This guide will get your AI LinkedIn Content Automation workflow up and running in n8n. Import Workflow Template: Download the template's JSON file and import it into your n8n instance via "File" > "Import from JSON." Configure Credentials: Google Gemini: Set up and apply your API key credentials to all "Google Gemini Chat Model" nodes. AI Image Generation (e.g., OpenAI): Create and apply API key credentials for your chosen image generation service to the "Generate an Image" node. LinkedIn: Set up and apply OAuth credentials to the "Create a post" node for your LinkedIn account. Customize Schedule & AI Prompts: Schedule Trigger: Double-click "Schedule Trigger 1" to set how often your workflow runs (e.g., daily, weekly). AI Prompts: Review and edit the prompts within the "Content Topic Generator," "Content Creator," and "Hashtag Generator / SEO" nodes to guide the AI for your desired content style and topics. Test & Activate: Test Run: Click "Execute Workflow" to perform a test run and verify all steps are working as expected. Activate: Once satisfied, toggle the workflow "Active" switch to enable automated posting on your defined schedule. Requirements To use this workflow template, you will need: n8n Instance: A running n8n instance (cloud or self-hosted) to import and execute the workflow. Google Gemini Account: For content topic generation, content creation, and hashtag generation (requires Google Gemini API Key) from Google AI Studios. AI Image Generation Service Account: For creating images (e.g., OpenAI DALL-E API Key or similar service that the "Generate an Image" node uses). LinkedIn Account: For publishing the generated posts (requires LinkedIn OAuth Credentials for n8n connection). Connect with us Website: https://www.intuz.com/cloud/stack/n8n Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz
by David Ashby
Complete MCP server exposing 3 IPQualityScore 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 IPQualityScore 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 IPQualityScore 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://ipqualityscore.com/api • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (3 total) 🔧 Json (3 endpoints) • GET /json/email/{YOUR_API_KEY_HERE}/{USER_EMAIL_HERE}: Email Validation • GET /json/phone/{YOUR_API_KEY_HERE}/{USER_PHONE_HERE}: Phone Validation • GET /json/url/{YOUR_API_KEY_HERE}/{URL_HERE}: Malicious URL Scanner 🤖 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 IPQualityScore 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 simonscrapes
Use Case Research search engine rankings for SEO analysis: You need to track keyword rankings for your website You want to analyze competitor positions in search results You need data for SEO competition analysis You want to monitor SERP changes over time What this Workflow Does The workflow uses ScrapingRobot API to fetch Google search results: Retrieves SERP data for your target keywords Captures URL rankings and page titles Processes up to 5000 searches with free account Organizes results for SEO analysis Setup Create a ScrapingRobot account and get your API key Add your ScrapingRobot API key to the HTTP Request node's GET SERP token parameter Either connect your keyword database (column name "Keyword") or use the "Set Keywords" node Configure your preferred output database connection How to Adjust it to Your Needs Modify keyword source to pull from different databases Adjust the number of SERP results to capture Customize output format for your reporting needs More templates and n8n workflows >>> @simonscrapes
by Lakshit Ukani
Who is this for? Content creators, social media managers, digital marketers, and businesses looking to automate video production without expensive equipment or technical expertise. What problem is this workflow solving? Traditional video creation requires cameras, editing software, voice recording equipment, and hours of post-production work. This workflow eliminates all these barriers by automatically generating professional videos with audio using just text prompts. What this workflow does This automated workflow takes video ideas from Google Sheets, generates optimized prompts using AI, creates videos through Google's V3 model via Fal AI, monitors the generation progress, and saves the final video URLs back to your spreadsheet for easy access and management. Setup Sign up for Fal AI account and obtain API key Create Google Sheet with video ideas and status columns Configure n8n with required credentials (Google Sheets, Fal AI API) Import the workflow template Set up authentication for all connected services Test with sample video idea How to customize this workflow to your needs Modify the AI prompts to match your brand voice, adjust video styles and camera movements, change polling intervals for video generation status, customize Google Sheet column mappings, and add additional processing steps like thumbnail generation or social media posting.
by David Ashby
Complete MCP server exposing all Mocean 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 Mocean Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Mocean Tool tool with full error handling 📋 Available Operations (2 total) Every possible Mocean Tool operation is included: 🔧 Sms (1 operations) • Send an SMS 🔧 Voice (1 operations) • Send an SMS 🤖 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 Mocean 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 Mocean 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
🛠️ Gotify Tool MCP Server Complete MCP server exposing all Gotify 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 Gotify Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Gotify Tool tool with full error handling 📋 Available Operations (3 total) Every possible Gotify Tool operation is included: 💬 Message (3 operations) • Create a message • Delete a message • Get many messages 🤖 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 Gotify 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 Gotify 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
🛠️ Twilio Tool MCP Server Complete MCP server exposing all Twilio 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 Twilio Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Twilio Tool tool with full error handling 📋 Available Operations (2 total) Every possible Twilio Tool operation is included: 🔧 Call (1 operations) • Make a call 🔧 Sms (1 operations) • Send an SMS/MMS/WhatsApp message 🤖 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 Twilio 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 Twilio 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
🛠️ Philips Hue Tool MCP Server Complete MCP server exposing all Philips Hue 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 Philips Hue Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Philips Hue Tool tool with full error handling 📋 Available Operations (4 total) Every possible Philips Hue Tool operation is included: 🔧 Light (4 operations) • Delete a light • Get a light • Get many lights • Update a light 🤖 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 Philips Hue 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 Philips Hue 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 Niklas Hatje
Use Case This workflow retrieves all members of a Discord server or guild who have a specific role. Due to limitations in the Discord API, it only returns a limited number of users per call. To overcome this, the workflow uses Google Sheets to track which user we received last to return all Members (of a certain role) from a Discord server in batches of 100 members. Setup Add your Google Sheets and Discord credentials. Create a Google Sheets document that contains ID as a column. We're using this to remember which member we received last. Edit the fields in the setup node Setup: Edit this to get started. You can read up on how to get the Discord IDs via this link. Link to your Discord server in the Discord nodes Activate the workflow Call the production webhook URL in your browser Requirements Admin rights in the Discord server and access to the developer portal of discord Google Sheets Minimum n8n version 1.28.0 Potential Use cases Writing a direct message to all members of a certain role Analysing user growth on Discord regularly Analysing role distributions on Discord regularly Saving new members in a Discord ... Keywords Discord API, Getting all members from Discord via API, Google Sheets and Discord automation, How to get all Discord members via API
by Michael
How it works it will return workflows that have buil-in nodes not of latest version with information of node name, type, current version and latest version for that type Set up steps: You need to have n8n credentials set, you can get n8n API key under settings set your instance base URL in "instance base url" node Disclaimar: Only check build-in nodes, community nodes are not supported
by Anderson Adelino
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Build intelligent AI chatbot with RAG and Cohere Reranker Who is it for? This template is perfect for developers, businesses, and automation enthusiasts who want to create intelligent chatbots that can answer questions based on their own documents. Whether you're building customer support systems, internal knowledge bases, or educational assistants, this workflow provides a solid foundation for document-based AI conversations. How it works This workflow creates an intelligent AI assistant that combines RAG (Retrieval-Augmented Generation) with Cohere's reranking technology for more accurate responses: Chat Interface: Users interact with the AI through a chat interface Document Processing: PDFs from Google Drive are automatically extracted and converted into searchable vectors Smart Search: When users ask questions, the system searches through vectorized documents using semantic search Reranking: Cohere's reranker ensures the most relevant information is prioritized AI Response: OpenAI generates contextual answers based on the retrieved information Memory: Conversation history is maintained for context-aware interactions Setup steps Prerequisites n8n instance (self-hosted or cloud) OpenAI API key Supabase account with vector extension enabled Google Drive access Cohere API key 1. Configure Supabase Vector Store First, create a table in Supabase with vector support: CREATE TABLE cafeina ( id SERIAL PRIMARY KEY, content TEXT, metadata JSONB, embedding VECTOR(1536) ); -- Create a function for similarity search CREATE OR REPLACE FUNCTION match_cafeina( query_embedding VECTOR(1536), match_count INT DEFAULT 10 ) RETURNS TABLE( id INT, content TEXT, metadata JSONB, similarity FLOAT ) LANGUAGE plpgsql AS $$ BEGIN RETURN QUERY SELECT cafeina.id, cafeina.content, cafeina.metadata, 1 - (cafeina.embedding <=> query_embedding) AS similarity FROM cafeina ORDER BY cafeina.embedding <=> query_embedding LIMIT match_count; END; $$; 2. Set up credentials Add the following credentials in n8n: OpenAI**: Add your OpenAI API key Supabase**: Add your Supabase URL and service role key Google Drive**: Connect your Google account Cohere**: Add your Cohere API key 3. Configure the workflow In the "Download file" node, replace URL DO ARQUIVO with your Google Drive file URL Adjust the table name in both Supabase Vector Store nodes if needed Customize the agent's tool description in the "searchCafeina" node 4. Load your documents Execute the bottom workflow (starting with "When clicking 'Execute workflow'") This will download your PDF, extract text, and store it in Supabase You can repeat this process for multiple documents 5. Start chatting Once documents are loaded, activate the main workflow and start chatting with your AI assistant through the chat interface. How to customize Different document types**: Replace the Google Drive node with other sources (Dropbox, S3, local files) Multiple knowledge bases**: Create separate vector stores for different topics Custom prompts**: Modify the agent's system message for specific use cases Language models**: Switch between different OpenAI models or use other LLM providers Reranking settings**: Adjust the top-k parameter for more or fewer search results Memory window**: Configure the conversation memory buffer size Tips for best results Use high-quality, well-structured documents for better search accuracy Keep document chunks reasonably sized for optimal retrieval Regularly update your vector store with new information Monitor token usage to optimize costs Test different reranking thresholds for your use case Common use cases Customer Support**: Create bots that answer questions from product documentation HR Assistant**: Build assistants that help employees find information in company policies Educational Tutor**: Develop tutors that answer questions from course materials Research Assistant**: Create tools that help researchers find relevant information in papers Legal Helper**: Build assistants that search through legal documents and contracts
by Diego
What this template does This workflow will read your Zotero Library and extract Meta Data from the articles of one collection in your bibliography. You can personalize the output for optimized results. How it works Mainly, follow the instructions in the Post it notes: Go to https://www.zotero.org/settings/security and find your USER ID (It's right under the APPLICATIONS Section. On the same website, create a New Private Key. In the "Collections" Node, select Generic Credential Type > Header Auth > Create New Credential using: NAME: Zotero-API-Key VALUE: [Your Private Key] Run your Flow to check if it works and open the "Select Collection" node. See the Results of the previous node as TABLE and copy the "KEY" of the collection you want to use. After that you should have a working flow that reads your bibliography. You can edit or delete the last 2 nodes to personalize your results (Filter and Edit Fields)