Workflow Templates

This n8n demonstrates how to build your own Github MCP server to personalise it to your organisation's repositories, issues and pull requests. This n8n implementation, though not as fully featured as the official MCP server offered by Github, allows you to control precisely what access and/or functionality is granted to users which can make MCP use simpler and in some cases, more secure. The use-case in this template is to simply view and comment on issues within a specific repository but can be extended to meet the needs of your team. This MCP example is based off an official MCP reference implementation which can be found here https://github.com/modelcontextprotocol/servers/tree/main/src/github How it works A MCP server trigger is used and connected to 3 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task. Behind these tools are regular Github nodes although preconfigured with credentials and targeted repository. The "Get Issue Comments" and "Create Issue Comment" tools depend on obtaining an Issue Number first. The agent should call the "Get Latest Issues" tool for this. How to use This Github MCP server allows any compatible MCP client to view and comment on Github Issues. You will need to have a Github account and repository access available before you can use this server. Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop Try the following queries in your MCP client: "Can you get me the latest issues about MCP?" "What is the current progress on Issue 12345?" "Please can you add a comment to Issue 12345 that they should try installing the latest version and see if that works?" Requirements Github for account and repository access. The repository need not be your own but you'll still need to ensure you have the correct permissions. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow Extend this template to interactive with pull requests or workflows within your own company's Github repositories. Alternatively, pull in metrics and generate reports for programme managers. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

This template provides a fully automated system for monitoring news on any topic you choose. It leverages Linkup's AI-powered web search to find recent, relevant articles, extracts key information like the title, date, and summary, and then neatly organizes everything in an Airtable base. Stop manually searching for updates and let this workflow deliver a curated news digest directly to your own database, complete with a Slack notification to let you know when it's done. This is the perfect solution for staying informed without the repetitive work. Who is this for? Marketing & PR professionals:** Keep a close eye on industry trends, competitor mentions, and brand sentiment. Analysts & researchers:** Effortlessly gather source material and data points on specific research topics. Business owners & entrepreneurs:** Stay updated on market shifts, new technologies, and potential opportunities without dedicating hours to reading. Anyone with a passion project:** Easily follow developments in your favorite hobby, field of study, or area of interest. What problem does this solve? Eliminates manual searching:** Frees you from the daily or weekly grind of searching multiple news sites for relevant articles. Centralizes information:** Consolidates all relevant news into a single, organized, and easily accessible Airtable database. Provides structured data:** Instead of just a list of links, it extracts and formats key information (title, summary, URL, date) for each article, ready for review or analysis. Keeps you proactively informed:** The automated Slack notification ensures you know exactly when new information is ready, closing the loop on your monitoring process. How it works Schedule: The workflow runs automatically based on a schedule you set (the default is weekly). Define topics: In the Set news parameters node, you specify the topics you want to monitor and the time frame (e.g., news from the last 7 days). AI web search: The Query Linkup for news node sends your topics to Linkup's API. Linkup's AI searches the web for relevant news articles and returns a structured list containing each article's title, URL, summary, and publication date. Store in Airtable: The workflow loops through each article found and creates a new record for it in your Airtable base. Notify on Slack: Once all the news has been stored, a final notification is sent to a Slack channel of your choice, letting you know the process is complete and how many articles were found. Setup Configure the trigger: Adjust the Schedule Trigger node to set the frequency and time you want the workflow to run. Set your topics: In the Set news parameters node, replace the example topics with your own keywords and define the news freshness that you'd like to set. Connect your accounts: Linkup: Add your Linkup API key in the Query Linkup for news node. Linkup's free plan includes €5 of credits monthly, enough for about 1,000 runs of this workflow. Airtable: In the Store one news node, select your Airtable account, then choose the Base and Table where you want to save the news. Slack: In the Notify in Slack node, select your Slack account and the channel where you want to receive notifications. Activate the workflow: Toggle the workflow to "Active", and your automated news monitoring system is live! Taking it further Change your database:* Don't use Airtable? Easily swap the *Airtable* node for a *Notion, **Google Sheets, or any other database node to store your news. Customize notifications:* Replace the *Slack* node with a *Discord, **Telegram, or Email node to get alerts on your preferred platform. Add AI analysis:** Insert an AI node after the Linkup search to perform sentiment analysis on the news summaries, categorize articles, or generate a high-level overview before saving them.

Who is this for? This workflow is for content creators, social media managers, marketing teams, and virtual assistants who want to automatically repurpose YouTube videos into ready-to-post social media content. If you need to quickly turn long-form videos into short posts for platforms like Instagram, Facebook, or LinkedIn, this workflow saves you hours of manual work. What problem is this workflow solving? Manually extracting ideas from YouTube videos, writing captions, creating images, and preparing social media posts takes a lot of time and effort. This workflow automates the entire process: it reads the video, generates posts with captions and AI images, and organizes everything into Airtable. It lets you focus more on growing your audience instead of spending hours repurposing content. What this workflow does Watches a YouTube channel RSS feed for new videos. Extracts the video transcript automatically using Dumpling AI. Summarizes and transforms the transcript into 3 social media captions (Instagram, Facebook, LinkedIn) using OpenAI. Generates 3 unique AI image prompts. Sends the prompts to Dumpling AI to create realistic social media images. Saves the captions and attaches the AI images into Airtable, ready for posting. Setup RSS Feed Setup Get your YouTube channel’s RSS feed URL. Insert the URL into the RSS Trigger node. This will monitor for new YouTube uploads automatically. Dumpling AI Setup for Transcript Extraction Sign up at Dumpling AI. Get your Dumpling AI API Key. In the first HTTP Request node after the RSS trigger, insert your API Key (use HTTP Header Authentication). This sends the YouTube URL to Dumpling AI’s /extract-transcript endpoint. OpenAI Setup for Caption and Prompt Generation Get your OpenAI API Key. In the OpenAI node, connect your account. The AI will: Generate 3 platform-specific captions. Generate 3 creative prompts to design images related to the video. Edit Fields Node This node organizes the generated captions and prompts into separate fields for easy Airtable mapping. Captions are split for Instagram, Facebook, and LinkedIn. Dumpling AI Setup for AI Image Generation After the Edit Fields node, the second HTTP Request node sends the image prompt to Dumpling AI’s /generate-image endpoint. This returns a realistic AI-generated image. Airtable Setup for Saving Posts (Without Image First) Create a new base in Airtable with the following fields: Platform (Single select: Instagram, Facebook, LinkedIn) Content (Long text field) Image (Attachment field) Connect your Airtable Personal Access Token to the Airtable node. The Airtable node saves the generated captions into separate records, initially without images. Upload Generated Images Back to Airtable The third HTTP Request node PATCHES the Airtable record. It updates the Image field with the generated AI image from Dumpling AI. Credentials Required Dumpling AI API Key (for transcript extraction and AI image generation) OpenAI API Key (for caption and prompt creation) Airtable Personal Access Token (for inserting and updating records) How to customize this workflow to your needs Change the OpenAI prompt to generate captions in your brand tone (e.g., friendly, professional, witty). Modify the image prompts to match your design style better. Adjust the Airtable base fields if you want to add more platforms or content formats. Add scheduling tools like Buffer or Metricool to automatically post from Airtable. ⚡ Quick Tips Make sure Dumpling AI credits are active to allow transcript and image generation. Set Airtable permissions properly so PATCH requests can update attachments.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Fetch SEO and traffic information from ahref for a list of domains in a Google Sheet. This is great for marketing research and SEO workflow optimizations and saves tons of time. How it works We'll import domains from the Google sheet We use an SEO MCP server to fetch data from ahref free tooling The fetched data is stored in the Google sheet Set up steps Copy Google Sheet template and add it in all Google Sheet nodes Make sure that n8n has read & write permissions for your Google sheet. Add your list of domains in the first column in the Google sheet Add MCP credentials for seo-mcp

What This Workflow Does This n8n workflow reads backlinks from a Google Sheet, sends each one to the DataForSEO On-Page API, and checks: Whether the backlink is still live on the target page Whether it's dofollow or nofollow Whether it's missing (i.e., lost) The result is then written back to the same Google Sheet under a Status column. Your result will look like this: Step-by-Step Setup Instructions Add your DataForSEO and Google Sheets credentials in n8n Make sure your Google Sheet has these columns: Backlink URL, Landing page, and Status Click the Test Workflow button to check a batch of backlinks Workflow Breakdown Trigger: Manual test start Read Data: Pulls backlink URLs and target pages from Google Sheets Format URLs: Extracts domain from URL Send POST Request to DataForSEO: Triggers a crawl on the backlink URL Wait 20 seconds: Allows crawl to finish Fetch Link Results: Retrieves backlink data from DataForSEO Validate Backlink: Checks if the backlink is live, and whether it’s dofollow Update Google Sheets: Logs the status as Live, Lost, or Lost (Nofollow)

This workflow helps SEO teams catch top movers in Google Search Console by comparing daily performance across keyword segments like brand, nonbrand, and content categories. Instead of serving as a routine check, it highlights the queries and pages with the biggest jumps or drops, making it ideal for spotting wins, losses, or unexpected shifts early. How It Works Runs daily on a scheduled trigger (e.g. every morning). Pulls GSC data for the prior two days (e.g. yesterday vs. day before). Segments traffic by keyword type or URL pattern (e.g. brand, nonbrand, recipes, blogs, etc.). Calculates changes in clicks, impressions, CTR, and average position. Flags top movers with the biggest positive or negative deltas. Sends structured reports via Slack or email, grouped by segment and sorted by impact. Setup Steps Connect your Google Search Console account and optionally Gmail or Slack. Swap in your own domain(s) and customize segmentation logic (e.g. brand terms, path filters). By default, the workflow includes Slack alerts, but these can be easily switched to or combined with email, webhook, or other channels. Full setup takes around 15–20 minutes with working GSC credentials. Note: The “recipes” segment is included as an example of how to segment content. This can be changed to match blog, FAQ, product pages, or any other category.

This n8n demonstrates how any organisation can quickly and easily build and offer MCP servers to their customers or internal staff to improve productivity. This MCP example uses PayCaptain.com as an example and shows how to create an MCP server which can search for and update employee data. How it works A MCP server trigger is used and connected to 3 custom workflow tools: Search Employee, Get Employee by ID and Update Employee. Each tool makes calls to the PayCaptain API to perform their respective tasks. Extra care is performed to strip out sensitive data and ensure we're not sharing too much. The Update Employee too also guards against updating fields which would preferably remain readonly. When you control the MCP server, you can determine behaviour of the tool. Finally, a Google Sheet node is used to log all operations for later audit. This will add a tiny bit of latency but recommended if sensitive data is being accessed. How to use This MCP server allows any compatible MCP client to manage their PayCaptain employee database. You will need to have a PayCaptain account and developer key to use it. Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop Try the following queries in your MCP client: "When did Sarah start here employment at the company?" "Does Jack work Wednesdays or Fridays?" "Please update Tracy's NI number to ABCD123456" Requirements PayCaptain Account and Developer Key. Google Sheets to log actions for later audit. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow Add or remove employee attributes as required for your user case. If Google Sheets is too slow, consider an API call to a faster service to log calls to the MCP server. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

How it works Simplified registration: Automatically captures sign-ups via optimized web forms. Instant confirmations: Immediately sends confirmation emails with event details and calendar invites. Scheduled reminders: Automatic reminder sequence before the event to maximize attendance. Post-event follow-up: Automatically collects feedback and nurtures participants. Set up steps Registration form: Create or connect your event registration form. Calendar system: Integrate with Google Calendar or Outlook to manage time slots. Email service: Set up your sending platform (Gmail, SendGrid, Mailchimp). CRM integration: Sync with your CRM for participant tracking. Feedback survey: Prepare your post-event satisfaction questionnaire. Personalized sequences: Tailor messages based on event type. Key Features 🎯 Optimized registration: Responsive forms with real-time validation 📅 Automatic calendar management: Instantly adds to calendars and manages time slots ⏰ Smart reminders: Progressive sequence (D-7, D-1, H-2) with personalized content 📊 Complete tracking: Monitors sign-ups, attendance, and participation rates 🎤 Multi-event support: Manage multiple events and formats simultaneously 📱 Mobile notifications: Push alerts and SMS for urgent reminders 🔄 Automatic feedback: Collects and analyzes participant feedback automatically 📈 Detailed analytics: Performance reports and improvement insights Supported Event Types Webinars**: Online sessions with auto-generated access links Conferences**: In-person events with seat and logistics management Trainings**: Learning sessions with progress tracking Meetings**: Internal meetings with invite coordination Workshops**: Practical sessions with materials and prerequisites Automated Sequence Sign-up → Immediate confirmation + calendar invitation D-7 → Reminder email with detailed program D-1 → Final reminder with practical info H-2 → Last-minute notification with access links/details Post-event → Satisfaction survey + additional content

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Prerequisites A n8n account (free trial available) A Scrapeless account and API key A Google account to access Google Sheets 🛠️ Step-by-Step Setup 1. Create a New Workflow in n8n Start by creating a new workflow in n8n. Add a Manual Trigger node to begin. 2. Add the Scrapeless Node Add the Scrapeless node and choose the Scrape operation Paste in your API key Set your target website URL Execute the node to fetch data and verify results 3. Clean Up the Data Add a Code node to clean and format the scraped data. Focus on extracting key fields like: Title Description URL 4. Set Up Google Sheets Create a new spreadsheet in Google Sheets Name the sheet (e.g., Business Leads) Add columns like Title, Description, and URL 5. Connect Google Sheets in n8n Add the Google Sheets node Choose the operation Append or update row Select the spreadsheet and worksheet Manually map each column to the cleaned data fields 6. Run and Test the Workflow Click "Execute Workflow" in n8n Check your Google Sheet to confirm the data is properly inserted Results With this automated workflow, you can continuously extract business lead data, clean it, and push it directly into a spreadsheet — perfect for outbound sales, lead lists, or internal analytics. How to Use ⚙️ Open the Variables node and plug in your Scrapeless credentials. 📄 Confirm the Google Sheets node points to your desired spreadsheet. ▶️ Run the workflow manually from the Start node. Perfect For: Sales teams doing outbound prospecting Marketers building lead lists Agencies running data aggregation tasks

How it works This comprehensive recruitment automation workflow transforms your hiring process from manual screening to intelligent candidate management. The system begins by automatically collecting CVs from multiple job boards and career platforms, immediately parsing each submission using advanced AI technology to extract key information including skills, experience levels, educational background, and career progression patterns. Once parsed, the workflow employs predictive scoring algorithms that evaluate each candidate against your specific job requirements and company culture criteria. This multi-dimensional analysis considers technical skills alignment, experience relevance, cultural fit indicators, and career trajectory patterns to generate compatibility scores with remarkable accuracy. The system then seamlessly transitions qualified candidates into automated interview scheduling, coordinating availability across hiring managers, team members, and candidates while optimizing for timezone considerations and calendar conflicts. Finally, successful candidates enter a personalized onboarding workflow that adapts to their role, department, and experience level, ensuring smooth integration into your organization. Target audience and problem solved This workflow is designed for HR departments, talent acquisition teams, and growing companies struggling with time-intensive recruitment processes. It specifically addresses the challenges of manual CV screening, subjective candidate evaluation, scheduling conflicts, and inconsistent onboarding experiences. Organizations processing high volumes of applications or seeking to eliminate recruitment bias while maintaining quality standards will benefit most from this automation. Set up steps Prerequisites: Ensure you have API access to your chosen AI parsing service (OpenAI, Affinda, or equivalent), active accounts on target job boards, and administrative access to your calendar and ATS systems. Configure job board integrations: Connect your LinkedIn Recruiter, Indeed, and Glassdoor accounts using their respective APIs. Set up webhook endpoints to automatically capture new CV submissions and configure filtering criteria based on job titles, locations, and basic qualifications. Establish AI parsing service: Choose and configure your CV analysis provider (OpenAI for natural language processing, Affinda for specialized CV parsing, or alternative services). Set up API credentials and define extraction templates for skills, experience, education, and custom fields relevant to your industry. Integrate calendar systems: Connect Google Calendar, Outlook, or your preferred scheduling platform. Configure availability windows for all hiring team members, set interview duration templates, and establish buffer times between meetings. Synchronize ATS platform: Link your Applicant Tracking System (Workday, BambooHR, Greenhouse, etc.) to ensure seamless candidate data flow. Map workflow fields to your ATS schema and establish status update triggers. Connect interview tools: Integrate video conferencing platforms (Zoom, Microsoft Teams, Google Meet) for automatic meeting room creation and invitation distribution. Configure recording settings and waiting room preferences. Link HRMS for onboarding: Connect your Human Resource Management System to trigger personalized onboarding sequences based on role type, department, and seniority level. Key Features 🧠 Advanced CV analysis**: Leverages machine learning to automatically extract and categorize skills, experience, education, certifications, and career progression patterns with 95% accuracy 📊 Multi-criteria scoring**: Implements customizable evaluation matrices considering technical skills, soft skills, experience relevance, cultural fit indicators, and growth potential 📅 Intelligent scheduling**: Automatically coordinates complex interview schedules across multiple stakeholders, considering time zones, availability preferences, and interview type requirements 🎯 Precise candidate matching**: Generates compatibility percentages based on job requirements, team dynamics, and long-term career alignment factors ⚡ Accelerated recruitment cycle**: Reduces time-to-hire by up to 60% through automated screening, intelligent prioritization, and streamlined communication workflows 👥 Collaborative evaluation**: Enables structured feedback collection from multiple interviewers with standardized scoring rubrics and consensus-building tools 📱 Enhanced candidate experience**: Provides mobile-optimized interfaces for application tracking, interview scheduling, and communication throughout the recruitment journey 🔄 Continuous optimization**: Automatically tracks and analyzes recruitment metrics to continuously improve scoring algorithms and process efficiency Customization options The workflow offers extensive customization capabilities including adjustable scoring weights for different criteria, industry-specific skill taxonomies, custom interview formats, and role-based onboarding paths. Organizations can configure approval workflows, set up custom notification templates, and establish specific integration parameters to match their unique recruitment processes and company culture. This automation solution transforms recruitment from a time-intensive manual process into a strategic, data-driven system that improves both hiring quality and candidate experience while significantly reducing administrative overhead.

Transform your local N8N instance into a powerful chat interface using any local & private Ollama model, with zero cloud dependencies ☁️. This workflow creates a structured chat experience that processes messages locally through a language model chain and returns formatted responses 💬. How it works 🔄 💭 Chat messages trigger the workflow 🧠 Messages are processed through Llama 3.2 via Ollama (or any other Ollama compatible model) 📊 Responses are formatted as structured JSON ⚡ Error handling ensures robust operation Set up steps 🛠️ 📥 Install N8N and Ollama ⚙️ Download Ollama 3.2 model (or other model) 🔑 Configure Ollama API credentials ✨ Import and activate workflow This template provides a foundation for building AI-powered chat applications while maintaining full control over your data and infrastructure 🚀.

📰 This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions. It aggregates headlines from 5 trusted sources and uses DeepSeek Chat to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader Tesla Quant Trading AI Agent system. ⚠️ Not standalone — this agent is designed to be executed by the Tesla Quant Trading AI Agent. ⚙️ Requires: DeepSeek Chat API Key 🔌 Workflow Role This tool processes Tesla-related news and produces output like: { "sentiment": "bullish", "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.", "topHeadlines": [ "Tesla beats Q2 delivery forecast – Yahoo Finance", "Cybertruck ramps up in Texas – Electrek", "Berlin Gigafactory expands battery production – CleanTechnica" ] } Its output feeds directly into the master trading agent’s final trade report. 📰 News Sources Used This agent collects real-time headlines from: Google News (filtered by “Tesla” or “TSLA”) Yahoo Finance (TSLA-specific feed) Electrek (Tesla archive) CleanTechnica (Tesla sustainability news) TeslaNorth (app/product release updates) These five tools are always queried together to ensure market-wide signal coverage. 🤖 What the Agent Does Pulls headlines from all 5 Tesla-specific RSS feeds Uses DeepSeek Chat to: Analyze narrative tone (bullish / bearish / neutral) Identify macro/financial drivers Generate a 2–3 sentence summary Return top 3–5 headlines Outputs structured JSON for downstream use 🛠️ Setup Instructions 1. Install & Name Import this file and name it: Tesla_News_and_Sentiment_Analyst_Tool 2. Add DeepSeek API Credentials Go to: Credentials → Add New → DeepSeek API Save as: DeepSeek account 3. Internet Access Required Ensure RSS feeds can fetch live headlines Works best with a cloud-hosted n8n instance or tunnel-enabled local install 4. Must Be Triggered by Parent Triggered via Execute Workflow by the Tesla Quant Trading AI Agent Requires these inputs: message: optional query context sessionId: passed to maintain short-term memory across executions 🧠 Agent Architecture | Node Name | Function | | ---------------------------------- | ------------------------------------------------ | | DeepSeek Chat Model | Performs AI-based sentiment analysis | | Tesla News and Sentiment Analyst | Combines results, formats output in strict JSON | | Simple Memory | Stores session-level context (short-term memory) | | 5x RSS nodes | Aggregate Tesla news from trusted media outlets | 📌 Sticky Notes Included 🟢 Trigger from Parent Workflow – Executed only by main TSLA agent 🟠 News Feeds Overview – Lists and explains each of the 5 feeds 🧠 DeepSeek Chat Notes – Describes LLM behavior and parsing role 🔵 Short-Term Memory – Buffers sentiment context during user session 📘 Sentiment Analyst Agent – Summarizes key responsibilities 📎 Licensing & Attribution © 2025 Treasurium Capital Limited Company This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization. 🔗 Creator: Don Jayamaha 🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/ 🚀 Power your TSLA trading with AI-driven sentiment—built with DeepSeek Chat and 5 trusted news sources. This tool is required by the Tesla Quant Trading AI Agent.