Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This n8n workflow integrates the powerful Pipedream MCP server with AI capabilities to create a smart, extensible assistant that can interact with over 2,700 APIs and 10,000+ tools — all within a secure and modular structure. This setup seamlessly integrates Pipedream's MCP server with n8n, enabling your AI assistant to leverage thousands of APIs and tools securely. Benefits Massive Tool Access**: Instantly connect 2,700+ APIs using Pipedream MCP tools — from productivity apps to custom APIs — with zero-code integration. Dynamic AI Agent**: The use of a LangChain agent allows for flexible tool execution and contextual conversations, powered by GPT. Easy Customization**: Simply copy your MCP tool URL into the respective sseEndpoint field to extend the agent’s capabilities. Scalable and Modular**: Add or remove tools (like Slack, Notion, Stripe, etc.) without altering the core logic. Secure and Revocable**: Credentials and API access can be managed directly via Pipedream’s MCP dashboard. How It Works Chat Trigger: The workflow begins when a chat message is received via the When chat message received node, which acts as the entry point. AI Agent Processing: The message is passed to the AI Agent node, which orchestrates the interaction using the connected tools and memory. Language Model: The OpenAI Chat Model (GPT-4.1-mini) processes the user's input and generates responses or actions. Memory: The Simple Memory node retains context from the conversation to enable coherent multi-turn interactions. Tool Integration: The Calendly and Gmail nodes (connected via Pipedream's MCP server) allow the AI to perform actions like scheduling events or sending emails. These tools use SSE (Server-Sent Events) endpoints provided by Pipedream. Response: The AI Agent combines the model's output and tool responses to deliver a final reply to the user. Set Up Steps Sign Up for Pipedream: Create an account on and set up your MCP server. Configure MCP Tools: Connect your accounts (e.g., Calendly, Gmail) in Pipedream and obtain the SSE endpoints for each tool (e.g., https://mcp.pipedream.net/xxx/calendly_v2). Update n8n Nodes: Replace the placeholder SSE endpoints in the Calendly and Gmail nodes with your Pipedream MCP URLs. OpenAI Credentials: Ensure the OpenAI Chat Model node has valid API credentials (configured under "OpenAi account"). Activate Workflow: Enable the When chat message received node (currently disabled) and deploy the workflow. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This guide walks you through building an intelligent AI Agent in n8n that routes tasks to the appropriate sub-agent using the new @n8n/n8n-nodes-langchain agent framework. You’ll create a Manager Agent that evaluates user input and delegates it to either an Email Agent or a Data Agent—each with its own role, memory, and OpenAI model. This is perfect for use cases where you want a single entry point but intelligent branching behind the scenes. 🔧 Step 1: Set Up the Manager Agent Start by dragging in an Agent node and name it something like ManagerAgent. This agent will act as the “brain” of your system, analyzing the user's input and determining whether it should be handled by the email-writing sub-agent or the data-summary sub-agent. Open the node’s settings and paste the following into the System Message: You are an AI Manager that delegates tasks to specialized agents. Your job is to analyze the user's message and decide whether it requires: An EmailAgent for writing outreach, follow-up, or templated emails, or A DataAgent for tasks involving data summaries, metrics, or analysis. Send the instructions to the sub agents. This instruction gives the Manager Agent clarity on what roles exist and what types of tasks belong to each one. 🧠 Step 2: Add Memory to the Manager Agent Drag in a Memory (BufferWindow) node and label it Manager Memory. Connect it to the ai_memory input of the Manager Agent. This ensures the agent can remember recent inputs and outputs from the user and agents during the conversation. No extra configuration is needed in this memory node—just connect it to the agent. 🔌 Step 3: Connect a Language Model to the Manager Agent Next, add a Language Model node and choose OpenAI Chat Model. Select a model like gpt-4o-mini or gpt-4, depending on what you have access to. Under Credentials, connect your OpenAI API key. If you haven’t created this credential yet: Click "OpenAI API" under Credentials. Choose "Create New". Paste your OpenAI API key (found at https://platform.openai.com/account/api-keys). Save it and return to the workflow. Once the model is set, connect it to the ai_languageModel input of the Manager Agent. ✉️ Step 4: Create the Email Agent Tool Now you’ll create a specialized sub-agent that only writes emails. Add an Agent Tool node and call it EmailAgent. In the tool’s settings, describe its job clearly. For example: Writes professional, friendly, or action-oriented emails based on instructions. Then scroll down to the System Message section and enter the following: You are a professional Email Writing Assistant. You write polished, effective emails for tasks such as outreach, follow-ups, and client communication. Follow the instruction provided exactly and return only the email content. Use a warm, business-appropriate tone. For the text input field, use the expression: {{ $fromAI('Prompt__User_Message_', ``, 'string') }} This allows the Email Agent to receive exactly what the Manager Agent wants it to handle. Add another Memory node and link it to this tool to help it maintain short-term context. Then add a second Language Model node, configured just like the first one (you can even clone it), and connect it to the EmailAgent. Finally, connect this entire EmailAgent setup back to the ManagerAgent by attaching it to its ai_tool input. 📊 Step 5: Create the Data Agent Tool Repeat the same steps, but this time for data summaries and analysis. Add another Agent Tool node and name it DataAgent. In the Tool Description, write something like: Responds to instructions requiring metrics, summaries, or data analysis explanations. For its input text field, you can use: {{json.query}} If desired, provide a system message that gives the agent more detailed instruction on how to behave: You are a helpful Data Analyst. Summarize trends, explain metrics, and break down data clearly based on user instructions. As with the EmailAgent, you’ll also need: A dedicated Memory node A dedicated Language Model node A connection to the ai_tool input of the Manager Agent Now the Manager Agent has two tools it can delegate to: one for communication and one for insights. 🧪 Step 6: Test Your AI Agent System Deploy the workflow and start testing by sending prompts like: > “Write a cold outreach email to a software company.” The ManagerAgent should route that to the EmailAgent. Then try: > “Summarize how our lead volume changed last month.” The DataAgent should receive that task. If routing isn’t working as expected, double-check your system messages and input bindings in each agent tool. ✅ You’re Done! You now have a modular, multi-agent AI system powered by n8n. The Manager Agent delegates intelligently, each sub-agent is optimized for its role, and all of them benefit from context memory. For more advanced setups, you can chain tools, add additional memory types, or use retrieval (RAG) tools for external document support.

A step-by-step demo that shows how to pull your Outlook calendar events for the week and ask GPT-4o to write a short summary. Along the way you’ll practice basic data-transform nodes (Code, Filter, Aggregate) and see where to attach the required API credentials. 1️⃣ Manual Trigger — Run Workflow | Why | Lets you click “Execute” in the n8n editor so you can test each change. | | --- | --- | 2️⃣ Get Outlook Events — Get many events Node type: Microsoft Outlook → Event → Get All Fields selected: subject, start API setup (inside this node): Click Credentials ▸ Microsoft Outlook OAuth2 API If you haven’t connected before: Choose “Microsoft Outlook OAuth2 API” → “Create New”. Sign in and grant the Calendars.Read permission. Save the credential (e.g., “Microsoft Outlook account”). Output: A list of events with the raw ISO start time. > Teaching moment: Outlook returns a full dateTime string. We’ll normalize it next so it’s easy to filter. 3️⃣ Normalize Dates — Convert to Date Format // Code node contents return $input.all().map(item => { const startDateTime = new Date(item.json.start.dateTime); const formattedDate = startDateTime.toISOString().split('T')[0]; // YYYY-MM-DD return { json: { ...item.json, startDateFormatted: formattedDate } }; }); 4️⃣ Filter the Events Down to This Week After we’ve normalised the start date-time into a simple YYYY-MM-DD string, we drop in a Filter node. Add one rule for every day you want to keep—for example 2025-08-07 or 2025-08-08. Rows that match any of those dates will continue through the workflow; everything else is quietly discarded. Why we’re doing this: we only want to summarise tomorrow’s and the following day’s meetings, not the entire calendar. 5️⃣ Roll All Subjects Into a Single Item Next comes an Aggregate node. Tell it to aggregate the subject field and choose the option “Only aggregated fields.” The result is one clean item whose subject property is now a tidy list of every meeting title. It’s far easier (and cheaper) to pass one prompt to GPT than dozens of small ones. 6️⃣ Turn That List Into Plain Text Insert a small Code node right after the aggregation: return [{ json: { text: items .map(item => JSON.stringify(item.json)) .join('\n') } }]; Need a Hand? I’m always happy to chat automation, n8n, or Outlook API quirks. Robert Breen – Automation Consultant & n8n Instructor 📧 robert@ynteractive.com | LinkedIn

This workflow fetches real-time air quality and pollen data using Ambee’s APIs and sends a friendly, personalized daily summary by email. It uses a scheduler to automate data collection, AI-generated health tips, and clear, actionable messages—perfect for sensitive users (e.g. kids with asthma, allergy sufferers). Use Case: Ideal for individuals with respiratory conditions, allergies, or those who want to stay informed about environmental conditions affecting their health.​ Set up steps Estimated time: 10–15 minutes You'll need: Ambee API key (free registration) OpenAI API key Email credentials (Gmail) User Profile 💡 Keep in mind: You’ll need to input your location coordinates (we’ve pre-filled Braunschweig as an example). The AI Agent node uses a ready-made prompt that’s tailored for email—but feel free to adapt it to other messaging platforms.

This workflow allows interactive conversation with the content of an XML file using OpenAI and LangChain. It fetches an XML feed from a specified URL, parses the XML, and enables an AI agent to respond to user queries based on the XML's structure and data. What It Does: Triggered via webhook or manual execution. Sets and fetches an external XML feed URL. Parses the XML into a readable format. Connects OpenAI GPT via LangChain for intelligent chat. AI agent answers questions like extracting nodes, attributes, or structure from the XML.

What It Does The Chef Agent is your AI-powered kitchen companion—ready to turn leftover ingredients into meal inspiration. It's a simple, fun n8n automation that: Accepts a list of ingredients via webhook Uses Ollama AI to suggest 5 creative recipes or food ideas Recommends up to 3 missing ingredients to improve the dish Returns a fallback message if the AI is unavailable Includes setup notes for beginners Requirements An active n8n instance (local or hosted) Ollama AI running locally (or another LLM via HTTP request) A webhook endpoint (defaults to /lets-cook) Why You’ll Love It Fully customizable for your use case or favorite LLM Great intro to AI + workflow automation Comes with playful Clown Mutiny flair: > “Powered by Clown Mutiny’s taste-bud liberation division.” Installation Import the provided JSON template into your n8n workspace. Configure your AI node to match your local Ollama instance. Trigger the flow by sending a POST request to the webhook: { "ingredients": "eggs, rice, spinach" }

This n8n workflow automatically fetches the latest CVE data at scheduled intervals, extracts relevant security details, and creates a corresponding Security Incident in ServiceNow for each new vulnerability. Schedule Trigger – Runs at predefined intervals. Jina Fetch – Retrieves the latest CVE feed. Information Extractor (OpenAI Chat Model) – Processes and extracts key details from the CVE data. Split Out – Separates each CVE entry for individual processing. Create Incident – Generates a ServiceNow Security Incident with the extracted CVE details. Ideal for security teams to ensure timely tracking and remediation of new vulnerabilities without manual monitoring.

This workflow is triggered when a new deal is created in HubSpot. Then, it processes the deal based on its value and stage. The first branching follows three cases: If the deal is closed and won, a message is sent in a Slack channel, so that the whole team can celebrate the success. If a presentation has been scheduled for the deal, then a Google Slides presentation template is created. If the deal is closed and lost, the deal’s details are added to an Airtable table. From here, you can analyze the data to get insights into what and why certain deals don’t get closed. The second branching follows two cases: If the deal is for a new business and has a value above 500, a high-priority ticket assigned to an experienced team member is created in HubSpot If the deal is for an existing business and has a value below 500, a low-priority ticket is created.

This workflow automates the process of summarizing or transcribing a WordPress article, converting the text into speech using Eleven Labs API, and uploading the resulting MP3 file back to WordPress. How It Works Trigger – The workflow starts manually when the user clicks “Test Workflow”. Retrieve Article – It fetches a WordPress article based on a given post ID. Summarize or Transcribe – An LLM (GPT-4o-mini) generates either: • A summary of the article, or • A full transcription, depending on the chosen prompt. Generate Speech – The processed text (summary or transcription) is converted into an MP3 audio file using Eleven Labs API. Upload MP3 to WordPress – The generated MP3 file is uploaded to WordPress. Update WordPress Post – The article is updated with an embedded audio player, allowing users to listen to the summary or transcription. Set Up Steps WordPress API Credentials • Configure your WordPress API credentials in n8n. Eleven Labs API Key • Obtain an API Key from Eleven Labs and configure it in n8n. Choose Between Summary or Transcription • Modify the AI prompt to either generate a summary or keep the full transcription. Test the Workflow • Run the workflow and ensure the MP3 file is correctly generated and uploaded. 💡 Customization Options • Modify the AI prompt to switch between a summary and a transcription. • Change the voice model in Eleven Labs for different speech styles. • Adjust output format to higher/lower quality MP3. 🚀 This automation improves content accessibility and engagement by allowing users to listen to a summarized or full version of the article. Phil | Inforeole

This n8n workflow automatically monitors RSS feeds for the latest AI vulnerability news, extracts key threat details, and creates a corresponding Security Incident in ServiceNow for each item. Schedule Trigger – Runs at scheduled intervals to check for updates. RSS Read – Fetches the latest AI vulnerability entries from the RSS feed. Read URL Content – Retrieves the full article for detailed analysis. Information Extractor (OpenAI Chat Model) – Parses and summarizes critical security information. Split Out – Processes each vulnerability alert separately. Create Incident – Generates a ServiceNow Security Incident with the extracted details. Ideal for security teams to track and respond quickly to emerging AI-related threats without manual feed monitoring.

An intelligent system that monitors social media conversations, identifies high-value engagement opportunities, and generates strategic comments to establish thought leadership while adding genuine value to discussions. Overview This automation workflow leverages Trigify's social listening platform to intelligently identify and respond to social media conversations. It combines AI-powered analysis with strategic comment generation to build authentic thought leadership presence across social platforms. 🔄 Workflow Process 1. Social Listening Webhook Real-time social media monitoring Integrated with Trigify.io social listening platform Monitors conversations across multiple social platforms Captures post content, author details, engagement metrics, and URLs Filters incoming posts by predefined keywords and topics Processes posts in real-time as they're discovered 2. Platform Validation Filter Platform-specific engagement optimization Checks post source (LinkedIn, Twitter, Reddit, etc.) Currently optimized for LinkedIn engagement Filters out non-relevant platforms Maintains platform-specific engagement strategies Routes posts based on platform requirements 3. Post Relevance Analyzer Agent AI-powered opportunity assessment Analyzes post content against expertise domains: Social Media Intelligence Competitive Analysis B2B Marketing Attribution Evaluates value-add potential and audience quality Scores engagement opportunity and confidence levels Identifies natural connection points to demonstrate authority Filters out low-quality or irrelevant conversations Returns structured analysis with TRUE/FALSE relevance decision 4. Engagement Decision Gate Quality control checkpoint Processes AI analysis results Only proceeds with TRUE relevance scores Prevents engagement on inappropriate content Maintains high-quality engagement standards Protects brand reputation through selective filtering 5. Strategic Comment Generator Agent Authentic thought leadership responses Generates comments under 30 words for maximum impact Focuses on tactical advice, strategic insights, or pattern recognition Avoids promotional language or forced statistics Incorporates domain expertise naturally Maintains conversational, helpful tone Uses experience-based insights over generic advice 6. Web Search Integration Enhanced context gathering Optional web search capability for additional context Provides current market insights when needed Supplements comment generation with real-time data Ensures comments are informed and relevant 7. Output Formatting Structured data preparation Compiles post URL, suggested comment, and post summary Formats data for Slack notification system Maintains context across workflow steps Prepares actionable engagement package 8. Slack Notification System Team collaboration and review Sends formatted notifications to #comment-strategy channel Includes post summary, suggested comment, and direct link Provides action buttons (View Post, Copy Comment, Skip) Enables team review before engagement Maintains engagement tracking and decision history 🛠️ Technology Stack n8n**: Workflow orchestration and webhook management Claude Sonnet 4**: Multi-agent AI analysis and content generation Trigify.io**: Social listening and post monitoring platform Slack API**: Team notifications and collaboration OpenAI API**: Optional web search for enhanced context Webhook Integration**: Real-time post processing ✨ Key Features Real-time social media monitoring via Trigify integration AI-powered relevance scoring and quality assessment Strategic comment generation focused on thought leadership Platform-specific engagement optimization (LinkedIn-focused) Team collaboration through Slack notifications Selective engagement to maintain high-quality interactions Expertise-based content analysis across multiple domains Anti-promotional safeguards for authentic engagement 🎯 Ideal Use Cases Perfect for professionals seeking to build authentic thought leadership: B2B Executives** building thought leadership presence Marketing Professionals** demonstrating industry expertise Sales Leaders** engaging prospects through valuable insights Consultants** establishing authority in their domains Business Development Teams** nurturing relationship building Companies** wanting systematic social media engagement Teams** requiring quality control over social interactions Professionals** seeking authentic network growth through value-add 📈 Business Impact Transform passive social listening into active thought leadership: Establishes thought leadership** through strategic engagement Builds authentic professional relationships** naturally Demonstrates expertise** without direct promotion Increases visibility** among target audience Creates networking opportunities** through valuable contributions Maintains consistent social media presence** systematically Scales personal engagement** while preserving authenticity This workflow ensures every engagement adds genuine value while naturally showcasing professional expertise, creating a sustainable approach to social media thought leadership.

Streamline client onboarding and project setup from hours to minutes with AI-driven automation. This intelligent workflow eliminates manual coordination, builds proposals, creates projects in Asana, welcomes clients on Slack, and logs everything — ensuring 90% faster onboarding and zero dropped steps. What This Workflow Does Transforms your client onboarding from scattered tools and emails into one seamless automation: 📝 Capture Client Details – Jotform intake form collects client, company, and project information. 🧠 AI-Powered Analysis – LangChain AI Agent analyzes the project scope, estimates effort, and recommends team composition. 📄 Generate Proposal – Automatically builds a professional HTML proposal summarizing goals, timeline, and estimated hours. 🗂️ Create Asana Project – Generates a new project with all key details, milestones, and assigned team members. 💬 Slack Collaboration – Creates a dedicated Slack channel, sends welcome messages, and introduces the project team. 📧 Welcome Email – Sends a personalized onboarding email to the client with project summary and next steps. 💼 CRM Sync – Creates or updates a HubSpot contact with complete project and client information. 📊 Audit Logging – Logs all onboarding activity to Google Sheets for centralized record-keeping. Key Features 🤖 AI Proposal Generation – Uses LangChain AI to generate smart project summaries and resource plans. ⚙️ End-to-End Automation – From form submission to project creation, communication, and CRM logging. 💬 Smart Slack Setup – Automatic channel creation and messaging for internal coordination. 📧 Personalized Client Emails – Beautifully formatted, professional onboarding emails. 🗂️ Asana Integration – Project creation with dynamic task templates and priorities. 📊 Google Sheets Logging – Instant audit trail for every client submission and generated proposal. 💼 CRM Integration – Automatically syncs client data with HubSpot for sales and account tracking. Perfect For 🚀 Agencies & Service Providers – Automate client onboarding, proposal creation, and task setup. 🏢 Consultancies – Quickly turn client requests into structured projects with assigned resources. 💻 Freelancers & Creators – Impress clients with AI-built proposals and instant communication. 📈 Growing Teams – Scale onboarding without extra admin or coordination time. 🧠 Operations Teams – Ensure consistency and transparency across all onboarding activities. What You’ll Need Required Integrations 🧾 Jotform – Client intake form (project details, budget, company info). Create your form for free on Jotform using this link 🤖 AI Agent – For analyzing project scope and building proposals. 🗂️ Asana – Project creation and task assignment. 💬 Slack – For automated client channel creation and internal communication. 📧 Gmail – For onboarding and proposal emails. 💼 HubSpot – CRM contact creation and project linkage. 📊 Google Sheets – For logging all onboarding and AI results. Optional Enhancements 📄 PDF Generation (PDF Munk) – Convert AI-generated proposals into downloadable PDFs. 💬 Slack Interactive Approvals – Add buttons for internal review before client communication. 📈 Performance Dashboard – Connect Google Sheets data to Looker Studio for tracking onboarding times. 🌍 Multilingual Support – Add translation nodes for international clients. 🔐 File Attachments – Send proposal PDFs or onboarding kits automatically via Gmail. Quick Start 1️⃣ Import Template – Copy and import the JSON file into your n8n workspace. 2️⃣ Set Up Jotform – Create a form with fields for client name, company, project name, budget, and requirements. 3️⃣ Add Credentials – Connect Jotform, AI Agent, Asana, Slack, Gmail, HubSpot, and Google Sheets. 4️⃣ Configure Sheet ID – Replace YOUR_SHEET_ID in the Google Sheets node. 5️⃣ Customize Proposal HTML – Edit AI prompt and branding to reflect your company’s style. 6️⃣ Test Workflow – Submit a test form and verify Slack, Asana, Gmail, and Sheets outputs. 7️⃣ Deploy – Activate workflow and share the Jotform link with your sales or operations team. Customization Options 1️⃣ Proposal Branding – Customize proposal HTML with logos, brand colors, and formatting. 2️⃣ AI Prompt Tuning – Refine the LangChain AI prompt to match your tone or project style. 3️⃣ Task Templates – Adjust task names, assignees, and due dates in the Asana creation node. 4️⃣ Slack Messaging – Update welcome message formatting and team introduction details. 5️⃣ CRM Fields – Map additional HubSpot properties for better data tracking. 6️⃣ Sheet Logging – Add more columns for tracking team recommendations or proposal scores. Expected Results ⚡ 90% Faster Onboarding – Reduce manual setup from hours to minutes. 🤖 AI Precision – Intelligent proposals and team allocations that impress clients instantly. 📈 Zero Missed Steps – Every project automatically created, communicated, and logged. 💬 Seamless Collaboration – Slack, Gmail, and Asana in perfect sync. 🗂️ Complete Transparency – Every onboarding step logged for accountability and improvement. 🏆 Use Cases 🧑‍💼 Marketing & Creative Agencies – Automate creative project scoping and proposal creation. 💻 Software Development Teams – Rapidly assess client tech requirements and allocate developers. 🧾 Consulting Firms – Build data-backed, AI-enhanced proposals for client engagements. 🏢 Corporate PMOs – Standardize project setup and approvals across multiple departments. Pro Tips 💡 Refine AI Prompt – Include examples of past projects to improve proposal quality. 💬 Add Slack Approvals – Insert “manager approval” logic before sending proposals. 📄 Attach PDFs – Use PDF Munk for branded, downloadable proposals. 📊 Track Conversion – Link HubSpot deal stage changes based on Asana progress. 📅 Monitor Efficiency – Use Sheet timestamps to calculate average onboarding time. Learning Resources This workflow demonstrates: AI integration using Agents Multi-app orchestration and data syncing Advanced HTML and email template customization Real-world Asana and Slack API usage CRM syncing and Google Sheets logging Modular, scalable n8n workflow design Workflow Structure Visualization 📝 Jotform Submission ↓ 🧠 AI Project Analysis (Agent) ↓ 📄 Proposal Generation (HTML) ↓ 🗂️ Asana Project Creation ↓ 💬 Slack Channel Setup & Message ↓ 📧 Gmail Welcome Email ↓ 💼 HubSpot Contact Creation ↓ 📊 Google Sheets Log Ready to Revolutionize Client Onboarding? Import this template today and let AI handle the heavy lifting. Your team saves hours, your clients get instant engagement — and your entire process runs flawlessly. ✨