Full-Stack Voice AI Agent with LiveKit, n8n and MCP on AWS | Udemy

Build your own end-to-end Voice AI Agent using LiveKit, n8n, and MCP — hosted on AWS.
This course guides you step by step in developing a real-time intelligent Voice AI system with automation, voice interaction, and web integration.

You’ll begin by setting up and configuring an Ubuntu server on AWS EC2, preparing your Python environment, and integrating LiveKit for real-time communication. Then, you’ll connect your AI Agent with n8n for workflow automation and MCP for multi-channel task handling — enabling features like voice-based appointment booking, email notifications, and calendar scheduling.

Once the backend is complete, you’ll build and deploy a React/Next.js frontend, secure it using NGINX and SSL certificates, and manage your application using PM2 and Systemctl .
By the end of the course, you’ll have a fully functional, secure, and automated Voice AI Agent deployed in a cloud environment.

Introduction

• What You’ll Learn

System Setup on AWS EC2

• Set Up and Configure an Ubuntu Server on AWS EC2
• Connect to Your AWS EC2 Instance Using MobaXterm
• Set Up the Project Directory
• Set Up Python Virtual Env

LiveKit Essentials: Setup, API Keys, and Configuration

• What is Livekit?
• Why LiveKit for Our AI Project?
• LiveKit Documentation Overview
• Installing LiveKit and Its Dependencies
• Create LiveKit Account
• Set Up Your OpenAI API Key
• Deepgram Account & API Setup
• LiveKit Plugins Setup

Build and Test Your AI Agent in LiveKit

• Build and Run the Agent Script (agent)
• Access via LiveKit Playground

Integrate prompts. py with AI Agent

• How prompts. py Works in the Project
• Add Task Definition
• Define Session Instruction
• Update agent. py Based on prompts. py
• Run Voice AI Agent

Integrating AI Avatars with Your Voice AI Agent

• What is an AI Avatar?
• How AI Avatar Integration Works
• Tavus Account & Persona Setup
• Add Tavus Persona IDs and APIs to .env
• Add Avatar in agent. py
• Rerun Voice AI Agent
• Test AI Avatar via LiveKit Playground

Configure AI Agent as a Systemctl Service

• Create a Systemctl Service File for the Voice AI Agent

Integrating LiveKit AI Agent with a Custom React Frontend

• Integrate with React Frontend
• Clone the React Project and Install Node.js
• Run the React App in Development Mode
• Access the React Frontend via EC2 Public IP

Deploy Next.js Frontend to Production Using PM2

• Overview of Next. js Production Deployment
• Build & Fix Build Issues
• Run with PM2
• Verfiy deployment

Purchase a Domain and Configure DNS Records

• Purchase a Domain from Godaddy
• Configure A Records

Secure the Application using NGINX and Let’s Encrypt SSL

• Overview of the Project
• Set Up and Configure NGINX
• Install Certbot Let’s Encrypt to Enable HTTPS
• Verify HTTPS Access
• Auto Renew SSL Certificates

Integrating AI Agent with n8n and MCP

• Overview: AI Agent with n8n and MCP
• Overview of n8n
• What is MCP?
• How It Works: AI Agent – MCP – n8n Flow
• Modify Agent Configuration for MCP Server
• Add an MCP Server Trigger Node in n8n
• Add a Google Calendar Node in n8n
• Fix Google Calendar Access
• Add Another Google Cal Node
• Add MCP Server URL in .env File on Server
• Restart Agent and Verify n8n Integration
• Modify prompts. py for Appointment Booking Flow
• Book an Appointment with Voice AI Agent
• Booking Validation: Prevent Double Appointments

AI Agent: Book the Appointment and Send Email Notification

• Add a Gmail Node in n8n workflow
• Set the Parameters in Gmail Node in n8n
• Modify prompts. py for Email Notifications
• Test the Voice AI Agent: Book Appointment and Send Email Notification

Integrate the Voice AI Agent with a Website (Smart Eye Clinic)

• Overview of the Project
• Clone Frontend Repo to Server
• Build Frontend — From Dev to Prod
• Run with PM2
• Add LiveKit APIs to .env.local
• Voice AI Testing — Smart Eye Clinic
• Last Lecture