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#005

In this episode of The Private AI Lab, Johan van Amersfoort is joined by Maxime Colomès to deep dive into the Model Context Protocol (MCP)—the emerging standard that is rapidly becoming the backbone for integrating AI models with real-world systems. Maxime shares hands-on experience building MCP servers in large enterprises, explains why MCP is often called the USB-C of AI, and explores how MCP enables private AI, secure enterprise integrations, and action-taking AI agents. The conversation also covers OpenShift AI, MLOps pipelines, security considerations, and future MCP use cases—from developer productivity to personal AI assistants. This episode is a must-watch for architects, platform engineers, AI practitioners, and anyone designing modern AI systems. 00:00 – Intro & welcome 02:40 – The story behind the podcast intro 03:46 – Who is Maxime Colomès? 04:45 – A day in the life: platform engineering & AI 06:32 – Funniest AI failures (and Jira chaos) 08:57 – What is Model Context Protocol (MCP)? 10:38 – MCP vs traditional APIs 11:39 – MCP architecture: clients & servers 12:49 – MCP and private AI 14:17 – Where MCP fits in enterprise AI architecture 17:26 – MCP primitives: tools, resources, prompts 19:02 – MCP donated to the Linux Foundation 22:22 – Why big tech agreeing on MCP matters 23:59 – Building MCP at enterprise scale 27:29 – Developers, chatbots, and multiple interfaces 30:18 – Security, permissions, and MCP gateways 34:56 – Challenges when adopting MCP 37:47 – MCP registries and community servers 41:19 – OpenShift AI and MLOps pipelines 44:51 – How to start small with MCP 47:39 – Consumer and personal AI use cases 52:40 – Sustainability, NGOs, and purpose-driven tech 56:47 – Key takeaways on MCP and private AI 59:36 – The “I told you so” MCP prediction 01:00:48 – Where to follow Maxime