AI · AIC-65

Agentic AI Development using n8n and MCP

Agentic AI Development using n8n and MCP is a 18-hour training course by IT Genius Institute. Traditional automation follows conditions written in advance, so it stalls on a message that does not fit the pattern or a question that needs data from…

Updated
From 7,110 THB / person 7,900 −10% excl. VAT 7% · group rates available
PDFDownload the course outline
  • Duration18 hours · 3 days
  • FormatOnsite / live online
  • Next roundOn request
  • LevelIntermediate

Course overview

Traditional automation follows conditions written in advance, so it stalls on a message that does not fit the pattern or a question that needs data from several places. Agentic AI changes this by letting an LLM interpret the request, plan, and choose which tools and data sources to use before it answers or acts. The real challenge is connecting that LLM to an organization's email, chat, databases and documents in a way that works reliably and stays under control.

This course uses n8n as the backbone for assembling AI agents and the Model Context Protocol (MCP) as the standard way for agents to reach tools and data. Learners start with the concepts of agentic AI and reasoning patterns such as ReAct, Reflexion and Chain-of-Thought, then build an AI email classification and reply system on n8n Cloud. They move on to self-hosting n8n Community Edition

with Docker, connect an MCP server to Slack and a Microsoft SQL Server database, and build a RAG system with Qdrant. Everything comes together as a customer service agent that answers from real transaction history and policy documents, handles multi-turn conversations, hands off to a human when needed, and is ready to scale into production. (3 days, 6 hours per day, 18 hours in total, Intermediate level.)

What you’ll gain

  • Explain the principles and components of agentic AI and the ReAct, Reflexion and Chain-of-Thought patterns
  • Understand the n8n architecture and choose between n8n Cloud and self-hosting
  • Install n8n Community Edition with Docker Compose and manage credentials securely
  • Connect an MCP server to n8n so agents can call tools and data
  • Integrate Gmail, Google Calendar, Slack and a Microsoft SQL Server database into workflows
  • Build a RAG system with Qdrant and OpenAI embeddings to search policy documents
  • Design and build a customer service agent that answers from real organizational data
  • Handle multi-turn conversations and human handoff, and tune the system before going live

Who this course is for

  • Developers who want to build AI agents connected to real organizational systems
  • Existing n8n users who want to move from automation to agentic AI
  • Business analysts and project managers designing automated customer service
  • IT and DevOps teams who install and operate self-hosted n8n
  • Anyone who wants AI to answer customers based on the organization's own data and policies

Prerequisites

  • Comfortable with computers and the basics of APIs, webhooks and JSON data
  • Some light coding experience helps, but you do not need to be a programmer
  • Gmail and Slack accounts for testing, plus an OpenAI API key with credit
  • A laptop that can run Docker Desktop (used on days 2 and 3) with permission to install software

Curriculum

Course Details

A 3-day course, 6 hours per day (18 hours in total, 09:00-16:00), delivered as lectures with labs that follow one continuous use case across all three days. Intermediate level. Day one runs on n8n Cloud; days two and three run on each learner's own machine with Docker. Learners bring their own Gmail and Slack accounts and an OpenAI API key with credit; OpenAI

API usage is billed by actual use. The course focuses on building AI agents with n8n and MCP rather than on workflow automation basics. Anyone who wants a solid n8n foundation first should take the separate n8n Workflow Automation for Modern Business course. Learners take home a lab guide, n8n workflow files for every lab, and docker-compose files for n8n, the MCP server, MSSQL and Qdrant.

Day 1 Agentic AI, n8n and an Intelligent Email System

Section 1: Agentic AI and How Agents Reason

  • What agentic AI means and how it differs from rule-based automation

  • Core components: perception, planning, reasoning, memory and action

  • ReAct: the agent alternates reasoning with tool calls until it reaches an answer

  • Reflexion: the agent reviews its own output and corrects it

  • Chain-of-Thought, and choosing a pattern that fits the task and the cost

  • Real use cases in customer service, document work and operations

Section 2: The n8n Architecture

  • Low-code / no-code workflow automation and where n8n fits

  • Core building blocks: nodes, connections, workflows and credentials

  • Runtime architecture and how workflows are executed

  • n8n Cloud compared with self-hosting

  • Community Edition compared with Enterprise Edition

Section 3: Key Nodes for Agentic AI

  • Trigger nodes: Webhook, Gmail and Schedule

  • AI nodes: OpenAI and Text Classifier for categorizing messages

  • Communication nodes: Gmail, Slack and HTTP Request

  • Data processing nodes: Code, JSON and Split in Batches

  • Database nodes (MSSQL, MongoDB) and utility nodes (IF, Switch, Merge)

Section 4: Lab: n8n Cloud and AI Email Classification

  • Sign up for and configure n8n Cloud, with good practice on the cloud platform

  • Connect Gmail and OpenAI credentials securely

  • Configure a Gmail trigger to bring new email into the workflow

  • Use Text Classifier to sort email into work, personal, travel and other

  • Use IF / Switch nodes to route each category down a different path

Section 5: Lab: Automated Email Replies and Scheduling

  • Connect an OpenAI model to the email classification workflow

  • Write prompts that draft replies with the right context and tone

  • Configure the Gmail node to send replies automatically

  • Create Google Calendar events from the content of an email

  • Test the whole workflow and check results in the execution log

Day 2 n8n on Docker, MCP and a RAG Knowledge Base

Section 6: Lab: Installing n8n Community Edition with Docker

  • Prepare the machine and install Docker and Docker Compose

  • Write and customize a docker-compose.yml file for n8n

  • Run n8n and open its web interface on your own machine

  • Configure environment variables and store credentials securely

  • Move workflows from n8n Cloud to the self-hosted instance

Section 7: Lab: MCP Server with n8n

  • MCP architecture: host, client, server and exposing tools to an agent

  • Install an MCP server with Docker and configure it

  • Connect the MCP server to n8n so the agent can call its tools

  • Test the MCP server and inspect the results of tool calls

Section 8: Lab: Connecting Slack to the Workflow

  • Create a Slack app and obtain an API token with only the scopes needed

  • Configure webhooks and Event Subscriptions so n8n receives messages

  • Connect Slack to an n8n workflow

  • Test sending and receiving messages through the Slack API

Section 9: Lab: MSSQL Database through MCP

  • Install Microsoft SQL Server on Docker and load sample customer data

  • Configure the database connection through the MCP server

  • Have the agent retrieve customer transaction data and test the results

  • Limit the database account so the agent can reach only what it needs

Section 10: Lab: A RAG System with Qdrant

  • The idea behind retrieval-augmented generation and why it helps question answering

  • Install the Qdrant vector database on Docker

  • Load customer service policy documents into Qdrant with OpenAI embeddings

  • Build the retrieval component and connect RAG to the MCP server

  • Test searching for the policies relevant to a customer's question

Day 3 A Customer Service Agent Ready for Real Use

Section 11: Designing the Customer Service Agent

  • Design the user flow and conversation sequence with the customer

  • Context management so the agent knows who it is talking to and about what

  • Designing the system prompt and prompts that keep answers within policy

  • Planning data handling and how answers are built from several sources

Section 12: Lab: Building the Customer Service Agent

  • Build a workflow that receives Slack messages and lets the agent interpret them

  • Retrieve the customer's transaction history from MSSQL through MCP

  • Search Qdrant for the relevant policies

  • Generate an answer from customer data and policy, then reply in Slack

  • Log the conversation history to MSSQL for later reference

Section 13: Lab: Handling Complex Conversations

  • Support multi-turn conversations

  • Strategies for retaining context across messages

  • Fallback when the agent is unsure, and handoff to a human agent

  • Refine prompts so answers follow policy consistently

Section 14: Performance Tuning and Scaling

  • Analyze performance and find bottlenecks in the workflow

  • Tune the Docker configuration for production

  • Scaling strategies for n8n and the MCP server as load grows

  • Guidance for taking the agent into real organizational use

Schedule & training options

For individuals — public rounds

No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770

For organisations — in-house / private

  • Tailor the content to your team’s tools and projects
  • Your dates, at your office or live online
  • Quotation with tax ID for procurement
Corporate training quote

Instructors

Frequently asked questions

Who is Agentic AI Development using n8n and MCP for, and what background is needed?

Built for Developers who want to build AI agents connected to real organizational systems · Existing n8n users who want to move from automation to agentic AI · Business analysts and project managers designing automated customer service Background you should have: Comfortable with computers and the basics of APIs, webhooks and JSON data · Some light coding experience helps, but you do not need to be a programmer Not sure the fit is right? Talk to our team on LINE @itgenius or call 02-570-8449.

How much does Agentic AI Development using n8n and MCP cost and how long does it run?

THB 7,900 (currently THB 7,110 on promotion). The course runs 18 hours. The price excludes 7% VAT (for payment in a company's name). Pay by bank transfer to the company account, confirm it on our payment page, and we can issue the receipt or tax invoice in your company's name.

Do I get a certificate?

Yes. Everyone who completes the course receives a Certificate of Completion from IT Genius Institute. Each certificate carries its own number, and anyone holding that number can verify it online on our certificate page, so you can add it to your portfolio or pass it to HR as evidence of training.

Where does the training take place, and is there an online option?

You can attend onsite at IT Genius Institute or arrange to join online, and we also run it as a private in-house session for your team. Ask about dates and venues on LINE @itgenius or call 02-570-8449.

What if I fall behind or miss a session — can I retake it?

Yes. You may retake the same course free of charge in a later round, under the institute's conditions. Tell our team which course and round you attended, and we will check it and offer you the rounds that still have seats. Ask us on LINE @itgenius or call 02-570-8449.

How do I enrol, or request a quotation for my company?

Enrol online with the registration form on this page. You can register several attendees at once and enter your tax ID and billing address for the tax invoice. Or request a company quotation straight from the quote button. For anything else call 02-570-8449 or reach us on LINE @itgenius.