A 22-step ai & agents automation, triggered by mcp server, sub-workflow, chat, connecting Google Calendar, HTTP / REST API, OpenAI (LLM), with built-in AI reasoning.
In plain terms: this is an AI assistant that works whenever someone chats with it. It uses AI to understand and generate content, so it handles judgement-style work, not just moving data. It connects to Google Calendar, OpenAI (LLM) and completes multi-step tasks for you automatically — the kind of work you'd otherwise hand to a virtual assistant.
22
Nodes
3
Integrations
18
Connections
MCP server, Sub-workflow, Chat
Trigger
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The real node graph exported from n8n — triggers (green), AI nodes (violet), services and logic — laid out as they run.
⚙️ How it works
SearchEvent· googleCalendarTool
CreateEvent· googleCalendarTool
UpdateEvent· googleCalendarTool
DeleteEvent· googleCalendarTool
Google Calendar MCP· mcpTrigger
When Executed by Another Workflow· executeWorkflowTrigger
Convert Text· toolWorkflow
When chat message received· chatTrigger
Simple Memory· memoryBufferWindow
Calendar MCP· mcpClientTool
My Functions· mcpClientTool
My Functions Server· mcpTrigger
Generate random user data· toolWorkflow
Random Jokes· toolWorkflow
💼 Business analysis
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Business use case
Deploys an autonomous AI agent that can reason over instructions, call tools, and take multi-step actions on behalf of a team — replacing repetitive knowledge work. It orchestrates Google Calendar, HTTP / REST API, OpenAI (LLM) so a single natural-language request becomes a completed task.
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Market need
Businesses are racing to put AI agents to work but lack the engineering to wire models to their real tools and data. This delivers that wiring as a ready-to-run asset.
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Market value
Custom AI-agent builds are quoted at $3,000–$15,000+ by agencies, with managed retainers on top. As a productised template it commands premium one-time or subscription pricing.