Milorad, n8n's MCP creator, joins the podcast to show you exactly how to get more out of the n8n instance-level MCP server, walking through three real builds from scratch, live on screen.

The episode is structured as a progressive masterclass: Level 1 is a deterministic form submission workflow with a data table and email notification, Level 2 is an AI agent that generates LinkedIn posts and can be triggered straight from your phone, and Level 3 is a multi-agent orchestration system where two models (Claude and GPT) independently review the same content and a third orchestrator merges their findings.

Along the way, they dig into the real reasons to pair n8n with an LLM client, including credential management, workflow observability, and the security tradeoffs baked into the MCP design. There's also a practical discussion on why iterating step by step beats trying to one-shot complex automations.

The conversation closes with a look at what's coming next, including chaining n8n MCP with third-party MCP servers, and an honest preview of what's still in development.

🎙 Chapters:
00:00 - What We're Building Today
00:20 - Three Levels of MCP Mastery
01:00 - Level 1: Building a Workflow via Chat
02:19 - Creating Data Tables and Form Triggers
08:20 - Adding Email Notifications to the Workflow
08:55 - Why Use n8n Alongside Claude
16:40 - Level 1 Complete: What You Can Do Now
17:26 - Level 2: Building an AI LinkedIn Post Agent
22:37 - Triggering Workflows From Your Phone
30:00 - Level 2 Wrap-Up and Human-in-the-Loop
30:01 - Security, Permissions, and Community Nodes
44:33 - Level 3: Multi-Agent Orchestration
44:37 - Two Models Reviewing the Same Content
42:00 - Building Iteratively vs. One-Shotting
44:31 - Level 3 in Action
42:01 - Connecting n8n MCP to Other MCP Servers
44:36 - Preview Status and What's Coming Next

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Get the open-source incident response workflow here: https://go.n8n.io/incident-response

Anthropic's Mythos AI just found a 27-year-old security bug in OpenBSD that no human ever caught. Days later the US government pulled both Mythos 5 and the public Fable 5 model, worried that same power could be weaponized into cyberattacks. The threat is no longer theoretical, and if your defense isn't automated too, you're already behind.

Dylan sits down with Viraj, a former n8n team member turned forward-deployed engineer, who now helps enterprise companies build AI-powered security systems. They walk through a live demo of an open-source cybersecurity workflow built with n8n and backed by real incident data.

The conversation covers how to bring AI into SecOps without letting it run wild, why historical incident data and playbooks matter more than the model you choose, and how Anthropic's Mythos is changing the threat landscape by chaining multiple vulnerabilities in a single attack. They also dig into real-world social engineering scams, phishing tactics, and why good data hygiene is the unsexy foundation that makes any AI system actually work.

The bigger takeaway: the models will keep getting smarter, but the companies (and individuals) who win are the ones with clean data, solid playbooks, and a workflow harness that can plug in whatever model comes next. This is a practical blueprint for fighting AI-powered threats with your own AI-powered defense.

🎙 Chapters:
00:00 - AI Found a 27-Year-Old Bug
00:37 - What the Demo Covers
02:43 - Test Incidents, Playbooks & Data
06:11 - Live Phishing Workflow Demo
07:08 - Three Branches of Analysis
09:35 - Threat Intelligence Explained
12:31 - Mythos and Zero-Day Threats
15:20 - Why Data Hygiene Matters
16:36 - Workflow Results Walkthrough
21:07 - Social Engineering and Scams
25:07 - Actionable Remediation Steps
30:53 - Data Ingestion for Companies
34:50 - Forward-Deployed Engineering
38:51 - Local Models and Personal Security
40:41 - Where to Find Viraj

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Most people hear about Claude's Cowork features and wonder how it actually fits into a real automation stack. This episode is the answer: a full walkthrough of connecting Claude Cowork to n8n, building a production-ready email classifier from scratch, and the token-saving tricks that make it all sustainable.

Ryan Nolan, who runs a data science YouTube channel and deploys AI automations at his day job, joins the n8n podcast to share his exact playbook for pairing these two tools.

The conversation covers setting up the n8n connector in under 60 seconds, calling external APIs through n8n workflows, building an email classifier with human-in-the-loop approval and error handling, and the new Google sign-in flow that eliminates the painful credential setup process. They also dig into why Claude's computer control is too slow for real scraping, and how n8n workflows are a better fit.

On the enterprise side, Ryan explains why compliance teams need structured execution logs (not just Cowork skill histories), how to roll out AI automation department by department, and the hackathon where a team with zero n8n experience built a driver's license verification workflow in two days.

🎙 Chapters:
00:00 - Introduction and episode overview
02:23 - Connecting n8n to Claude Cowork
04:21 - Calling APIs from Cowork via n8n
10:27 - Building an email classifier workflow
14:51 - Tips for prompting and iterating
13:42 - Compliance and audit logging
24:10 - Saving tokens with n8n workflows
32:31 - Enterprise security and skills vs workflows
36:48 - Reviewing the built workflow
39:41 - Quick Google credential setup
42:10 - Execution history and debugging
44:01 - The hackathon story
46:45 - Advice for getting started
51:43 - Running with David Goggins

Get 30% Off n8n Cloud Starter or Pro Plans!
Want to get started with n8n? Visit n8n.io/pricing and use code 2025-N8N-PODCAST-729C416E at checkout for 30% off your first month or year.