Build an AI marketing team with OpenAI O3 and GPT-4.1-mini for automated content creation
🧠 Overview This multi-agent n8n automation simulates a high-functioning marketing team. A strategic CMO agent receives your chat-based input, decides which specialist is best for the task, and delegates accordingly. Each specialist (copywriter, SEO expert, brand strategist, etc.) operates independently using fast, cost-effective GPT-4.1-mini models—resulting in parallel task execution and full-funnel marketing output with minimal human input. --- ⚙️ How It Works A chat message trigger listens for input (e.g. “Write a full email funnel for our SaaS launch”). The CMO Agent (powered by OpenAI O3) reads the message and determines intent, strategy, and needed outputs. It dynamically delegates tasks to the correct AI agent: Copywriter Agent Facebook Ads Specialist SEO Content Writer Email Marketer Social Media Manager Brand Voice Specialist Each agent uses a dedicated GPT-4.1-mini model to produce results instantly. Final content is returned to the user or passed along for integration with your CMS, ad platforms, or CRM. --- 🧰 Tools Used n8n – Orchestrates the entire agent communication and routing logic OpenAI O3 – Advanced strategic reasoning (CMO Agent) OpenAI GPT-4.1-mini – Fast and cost-efficient for specialist agents LangChain Nodes – For multi-agent thinking and tool-based execution --- 🚀 Quick Start Import Workflow: Load the provided .json into your n8n instance Set Credentials: Add your OpenAI API key under “OpenAI Account” Deploy Webhook: Use the “When Chat Message Received” trigger Test It: Ask a question like: > “Generate a 7-day onboarding email sequence for a weight loss app” Watch the Agents Collaborate! --- 👩💼 Meet Your AI Marketing Team | Agent | Purpose | Model | Output | |-------|---------|-------|--------| | 🧠 CMO Agent | Strategy, delegation, and task routing | O3 | Central brain | | ✍️ Copywriter Agent | Website copy, CTAs, product descriptions | GPT-4.1-mini | Fast, human-like copy | | 📱 Facebook Ads Copywriter | Ad headlines, angles, A/B tests | GPT-4.1-mini | Platform-specific ad copy | | 🔍 SEO Writer | Blog posts, keyword-rich content | GPT-4.1-mini | Long-form content | | 📧 Email Specialist | Sequences, newsletters, welcome flows | GPT-4.1-mini | Funnel-ready emails | | 📲 Social Media Manager | Content calendars, posts, hashtags | GPT-4.1-mini | Cross-platform content | | 🎨 Brand Voice Specialist | Tone consistency, style guides | GPT-4.1-mini | On-brand text | --- 💡 Use Cases Product Launches: Strategy → Landing Page → Emails → Social Posts Lead Nurture Funnels: Segmented email campaigns with consistent tone Content Sprints: Generate 30+ blog posts and socials in a day Ad Variations: Create 20 ad angles in 30 seconds Brand Guidelines: Enforce consistent messaging across departments --- 💸 Cost Optimization Use O3 sparingly—only for strategic tasks All specialist agents use GPT-4.1-mini for low-latency, high-efficiency generation Run agents in parallel to reduce wait times Add caching for repeat requests --- 🔧 Customization Tips Edit the tool prompts to match your brand’s style and niche Connect outputs to Google Sheets, Notion, Slack, or email tools Integrate with Zapier, Make.com, or your CRM for full automation --- 🔗 Connect With Me Website: nofluff.online YouTube: @YaronBeen LinkedIn: Yaron Been --- 🏷️ Tags n8n OpenAI MarketingAI CMOagent Automation GPT4 LangChain NoCode MarketingTeam AIWorkflow EmailMarketing SEO Copywriting SocialMedia DigitalMarketing BrandVoice AItools MultiAgentSystem ContentCreation MarketingStrategy ContentOps
By Yaron BeenExport Zammad objects (users, roles, groups, organizations) to Excel
This n8n workflow enables you to export data from Zammad, including Users, Roles, Groups, and Organizations, into individual Excel files. It simplifies data handling and reporting by creating structured outputs for further processing or sharing. Features Export Users with associated details such as email, firstname, lastname, roleids, and groupids. Export Roles and Organizations with their respective identifiers and names. Convert all data into separate Excel files for easy access and use. Usage Import this workflow into your n8n instance. Configure the required Zammad API credentials (zammadbaseurl and zammadapikey) in the Basic Variables node. Run the workflow to generate Excel files containing Zammad data. Issues and Suggestions If you encounter any issues or have suggestions for improvement, please report them on the GitHub repository. We appreciate your feedback to help enhance this workflow!
By SirhexalotFile hash verification for AI agents with hashlookup CIRCL API
Complete MCP server exposing 11 hashlookup CIRCL 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 hashlookup CIRCL 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 hashlookup CIRCL 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://hashlookup.circl.lu • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (11 total) 🔧 Bulk (2 endpoints) • POST /bulk/md5: Bulk Search MD5 Hashes • POST /bulk/sha1: Bulk Search SHA1 Hashes 🔧 Children (1 endpoints) • GET /children/{sha1}/{count}/{cursor}: Return children from a given SHA1. A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0. 🔧 Info (1 endpoints) • GET /info: Get Database Info 🔧 Lookup (3 endpoints) • GET /lookup/md5/{md5}: Lookup MD5. • GET /lookup/sha1/{sha1}: Lookup SHA-1. • GET /lookup/sha256/{sha256}: Lookup SHA-256. 🔧 Parents (1 endpoints) • GET /parents/{sha1}/{count}/{cursor}: Return parents from a given SHA1. A number of element to return and an offset must be given. If not set it will be the 100 first elements. A cursor must be given to paginate over. The starting cursor is 0. 🔧 Session (2 endpoints) • GET /session/create/{name}: Create a session key to keep search context. The session is attached to a name. After the session is created, the header hashlookup_session can be set to the session name. • GET /session/get/{name}: Return set of matching and non-matching hashes from a session. 🔧 Stats (1 endpoints) • GET /stats/top: Get Top Queries 🤖 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 hashlookup CIRCL 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 David Ashby