https://video.ut0pia.org/videos/watch/72e5c305-4e24-4f9c-9ca3-2d68cc7dc4cf Tun Shwe and Jeremy Frenay from Lenses.io address the critical security and design challenges involved in moving Model Context Protocol (MCP) servers from local development to enterprise production. Effective agentic design is inseparable from security and here we propose five core principles such as shrinking the attack surface, constraining inputs and returning only essential data. Standard local setups fail under professional workloads, necessitating a shift to remote MCP servers and robust authentication frameworks. Detailed technical flows are provided for OAuth 2.1, comparing Dynamic Client Registration (DCR) with the more advanced Client ID Metadata Document (CIMD) approach for managing agent identities. Come learn how to adopt the correct mindset for building enterprise-grade agentic AI systems with MCP. https://github.com/lensesio/lenses-mcp https://lenses.io/ Tun Shwe - Staff AI Engineer, Lenses.io Tun is a Staff AI Engineer at Lenses.io, where he leads AI strategy. He is focused on helping companies imagine and implement their strategic vision with agentic AI systems fuelled with real-time context. He was previously a Head of Data and Data Engineer at high growth startups and has spent 20 years building data-intensive applications and leading T-shaped teams. In his spare time, Tun goes surfing, plays guitar and tends to his analogue cameras. -- Jeremy Frenay is an AI Engineer at Lenses.io, where he works on bringing AI-assisted engineering to the Apache Kafka ecosystem. Previously, Jeremy co-founded Arcane, an AI copilot for marketers, and led data operations engineering at Babylon Health, scaling data platforms for one of the world's largest healthtech unicorns. Socials: https://lenses.io/ https://github.com/lensesio/lenses-mcp https://www.linkedin.com/in/tunshwe/ https://www.linkedin.com/in/jeremy-frenay/ Slides: https://drive.google.com/file/d/1zLzkVO7_kBoV6bI7lhYIi3AxUH6j7xH_/view?usp=sharing Thu, 09 Apr 2026 15:12:33 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.ut0pia.org https://video.ut0pia.org/lazy-static/avatars/0287a09a-aae7-4840-9843-b416426e7046.webp https://video.ut0pia.org/videos/watch/72e5c305-4e24-4f9c-9ca3-2d68cc7dc4cf All rights reserved, unless otherwise specified in the terms specified at https://video.ut0pia.org/about and potential licenses granted by each content's rightholder.