Documentation is one of the most important parts of building automation systems. It is also one of the most tedious. In this video, I show a system that turns a walkthrough video plus a workflow screenshot into a clean, structured Google Doc. No more writing SOPs from scratch. What the system produces: - A well formatted Google Doc - Clear sections for setup, nodes, APIs, and deployment notes - Screenshot placeholders so you know exactly where visuals should go - A production checklist you can use before shipping How it works, step by step: 1. Submit a form - Video URL (YouTube or an unlisted upload) - Workflow screenshot (file upload) 2. Extract the screenshot for later use - Convert the uploaded image into a base64 string - Store it so it can be referenced further down the workflow 3. Pull the video transcript with Apify - Run the YouTube Transcript Scraper - Return the transcript data 4. Clean the transcript with a Code node - Combine all transcript segments into a single readable paragraph 5. Convert the stored screenshot back into a file - Move base64 back into a file so it can be analyzed 6. Analyze the workflow screenshot with OpenAI - Generate a structured description of what the workflow is doing 7. Generate the documentation with Claude via OpenRouter - Feed it two inputs: - Transcript text - Workflow screenshot description - Output a JSON with: - Documentation title - Full markdown documentation 8. Parse the JSON output - Split out title and documentation fields cleanly 9. Create a Google Doc from Markdown - Use a community node that supports Markdown to Google Docs formatting - Auto-create the doc in the correct Drive folder Result: You record a 10 minute walkthrough, upload one screenshot, and the system drafts the entire doc for you. If you want to build it, the blueprint and prompts are linked in the description. Subscribe for more tutorials on n8n systems, AI agents, and agency-ready automations. https://youtu.be/a7O2-axMJEg?si=dRkeaTigxgVLyzLI

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Voice AI agents have come a long way. What used to take a bunch of custom tools and webhook wiring can now be done much faster using MCP. In this video, I show how to build a simple AI receptionist that: - Answers calls - Collects customer info - Checks availability - Books appointments into Google Calendar - Saves the customer record into Google Sheets - Sends a confirmation email Here is the flow, step by step: 1. Set up the voice agent in Vapi - Use GPT 4.1 mini for lower cost and faster responses - Make the assistant speak first - Add a system prompt with identity, tone, and tool instructions 2. Connect Vapi to n8n using MCP - Add an MCP Server Trigger in n8n - Build your tools as sub workflows - In Vapi, create an MCP tool and paste the MCP server URL - Add an Authorization header using your n8n API key 3. Create the sub workflows (these become your tools) - Get user - Search the Google Sheet by email - If not found, return “new client” so the agent knows to create them - Create user - Append a new row with name, phone, email, and call date - Get available slots - Pull calendar events for the requested date - Return busy times between business hours (example 9:00 AM to 5:00 PM) - Book appointment - Create the Google Calendar event - Update the user row with service type and appointment time - Send a confirmation email 4. Let the model fill tool parameters automatically - In the MCP trigger inputs, use “defined automatically by the model” - This avoids extra agents and reduces latency and cost 5. Test the full experience end to end - Call the number - Book an appointment - Confirm the data shows up in Sheets and Calendar - Confirm the email is sent If you want to build this exact setup, I included the resources and workflows in the description. Subscribe for more tutorials on voice AI agents, MCP, and real automations you can deploy. https://youtu.be/IiTV70i-2zA?si=IQAZEllSWNTqoPyH

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