Quick update: the community is now broader and more practical. We’re moving from a tool-specific focus to AI automation as a whole: agents, workflows, integrations, internal tools, browser automation, APIs, and real business systems. That means we’ll cover whatever fits the job: Hermes, n8n, Claude, Codex, OpenAI, Make, Zapier, OpenClaw, custom scripts, and more. The goal stays simple: build automations that save time, improve operations, and create real leverage.

Let’s get to know each other. Comment below with: - where you are in the world - what you’re building or want to automate - your current AI automation stack, if you have one - the biggest workflow or business process you want to improve - and something you like to do for fun 😊

n8n is proud to announce the release of native MCP integration, empowering you to revolutionize how AI agents interact with your workflows. This game-changing update introduces two powerful new nodes that will take your automation to the next level. What’s New? 1. MCP Client Tool 2. MCP Server Trigger Why This Matters - Standardize AI Interactions: MCP acts as a universal connector, solving integration challenges and enabling AI agents to interact with tools and data sources seamlessly. - Enhance Workflows: Let AI agents execute n8n workflows, monitor executions, and pass parameters dynamically for more intelligent automation. - Future-Proof Your Automation: Build agentic systems that adapt to diverse tools and data sources without custom code, ensuring your workflows stay agile and efficient. Get Started Today! - Access: Available on the next branch (non-production) – update your n8n instance to start exploring. Note: Ensure to apply the right level of security.

Hey Skool Community! As AI agencies, we're revolutionizing how small businesses operate, but pricing these services can be tricky. Let's explore some popular models and discuss how we can tailor them to meet client needs: 1. Project-Based Pricing: Ideal for one-time setups like chatbots or workflows ($300-$10,000). 2. Subscription Models: Monthly fees for ongoing support ($50-$750). 3. Performance-Based Pricing: Tie fees to results (e.g., $50-$3,000 per lead/sale). 4. Hybrid SaaS Model: Combine flat fees with performance bonuses. What are your favorite pricing strategies? How do you balance affordability with the value you deliver? Let's share insights and collaborate on creating effective pricing frameworks! Share Your Thoughts: - What challenges have you faced with pricing AI services? - How do you ensure your pricing reflects the value you bring to clients? - Are there any innovative models you're using or exploring? Let's work together to create a comprehensive guide for pricing AI services that benefits everyone in our community!

Awesome MCP servers for AI Agents! (300+ open-source MCP servers) Awesome MCP Servers is a curated list of production-ready and experimental MCP servers to supercharge your AI models. Key Features: ⚙️ Standardized server implementations 🔑 Secure and flexible local or remote deployments 🎖️ Supports Python, Go, Rust, and more. Server implementations span various domains: 💰 Finance 🤾🏼‍♂️ Sports 🧭 Travel 📂 Browser automation 🧠 Knowledge management and more... The best part it's 100% open-source, link to the GitHub repo in comments. https://github.com/punkpeye/awesome-mcp-servers Also adding WhatsApp MCP (I have not tested it yet) https://github.com/lharries/whatsapp-mcp