10 Cities. 4 Countries. One Unexpected MCP Lesson.

10 Cities. 4 Countries. One Unexpected MCP Lesson.

Author: Demetrios July 6, 2026 Duration: 22:18

In this episode, we're joined by Ben Morss, Developer Advocate at DeepL, who spent months traveling across North America and Europe teaching developers about MCP, building MCP servers, and helping teams understand how AI agents actually use tools.


We dive into the biggest misconceptions around MCP, why so many developers still misunderstand how it works, and what Ben learned after giving talks and workshops in 10 cities across four countries. Along the way, we explore MCP server design, tool calling, security concerns, translation workflows, developer education, and how DeepL is using MCP to bring high-quality language translation into AI-powered applications.


DeepL: https://www.deepl.com


Ben Morss: https://www.linkedin.com/in/ben-morss-ph-d-15bab15/

Alex Salkever: https://www.linkedin.com/in/alexsalkever


Timestamps:

[00:00] AI and API Integration

[00:41] DeepL at DevSummit

[01:19] MCP Roadshow Origins

[03:47] MCP Hackathon Insights

[07:52] Security in Model Protocols

[10:25] AI Expert vs Noob Queries

[16:08] DeepL vs Frontier LLMs

[18:16] MCP vs REST API

[21:39] MCP Servers and DeepL


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 50

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