Advanced automation developers and AI architects who want to scale their AI systems beyond single-task bots into a collaborative ecosystem of specialized agents.

Proficiency in n8n workflow design and a solid understanding of LLM “Tools.” Familiarity with the concept of an API is essential

Course Outline:

1. MCP Mastery: The New Standard for Skills
   1. What is MCP? Understanding the Model Context Protocol and why it’s the “USB-C for AI Tools.”
   2. Universal Skillsets: Turning local scripts and external APIs into standardized MCP servers
   3. Connect n8n with MCP: How to give any agent instant access to a library of pre-built capabilities
   4. Lab: : Connecting a local MCP server to an n8n Agent node to perform a system-level task

2. Modular Design: Building the Agent Team
   1. The “Manager” Pattern: Using a high-reasoning model (e.g., GPT-4o or Gemini) to orchestrate smaller, faster models
   2. Executing Sub-workflows: How to call an independent n8n workflow as a “Tool.”
   3. Inter-Agent Communication: Passing state and context between a “Writer Agent” and a “Fact-Checker Agent.”
   4. Lab: Creating a “Reviewer Loop” where a second agent critiques and improves the first agent’s output

3. Production Hardening: Reliability & Oversight
   1. Human-in-the-Loop (HITL): Using “Wait” nodes and “Wait for Webhook” to pause for manual approval
   2. Error Handling & Retries: Building “Self-Healing” workflows that retry LLM failure or API timeouts
   3. Observability: Monitoring token usage, costs, and execution latency within n8n
   4. Lab: Adding a Slack/Email approval step to an autonomous publishing pipeline

Training material provided: Yes (Digital format)

Hands-on Lab: Students will be provided with docker compose file and n8n workflow JSON.