MCP Goes Stateless

MCP Goes Stateless

Author: Demetrios July 27, 2026 Duration: 52:27

David Soria Parra is an Engineering Lead at Anthropic and one of the core maintainers of the Model Context Protocol (MCP). We explore the biggest evolution of the protocol since its launch, and why MCP is becoming the foundation for the next generation of AI agents.


We discuss why MCP is moving toward stateless communication, what developers misunderstand about state, sessions, and transport layers, and how lessons from real-world deployments at massive scale have shaped the protocol's future. We also dive into MCP v2, SDK migrations, protocol design, extension architecture, governance, developer experience, and how Anthropic thinks about balancing simplicity with long-term flexibility.


Along the way, we explore progressive disclosure, tool search, programmatic tool calling, context bloat, forward compatibility, long-running AI tasks, protocol evolution, open-source governance, observability, and why the future of AI infrastructure will depend on designing protocols that can evolve without breaking the ecosystem.


Timestamps:

[00:00] Introduction

[01:59] Why MCP Had to Become Stateless

[04:28] The Tradeoffs of Stateless Design

[06:13] What We Learned About Agent State

[08:04] Sessions, Models & Implicit State

[09:33] Migrating to MCP v2

[12:19] Lessons from HTTP & Open Source Standards

[18:16] Shipping Fast Without Breaking Everything

[20:35] The Future Complexity of MCP

[22:44] Core Features vs Extensions

[26:47] Progressive Disclosure Explained

[28:16] Solving Context Bloat

[30:50] Why Tool Search Beats Progressive Disclosure

[32:10] The Biggest MCP Anti-Pattern

[34:25] Designing for Forward Compatibility

[38:41] Why "Tasks" Matter

[40:53] JSON, Tokens & Better Tool Calling

[44:44] Observability & Tracing AI Agents

[47:34] Will MCP Ever Be Finished?

[50:22] What's Next for MCP


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

Agentic Conversations (formally mlops.community)
Podcast Episodes
Inside Just Eat's AI Lab: Voice Agents & Agentic Commerce [not-audio_url] [/not-audio_url]

Duration: 1:18:38
Guthrie Cooper (Senior Group Product Manager, AI & Robotics) and Nidhi Sharma (Global Head of Engineering AI & Incubation) from Just Eat Takeaway.com join the MLOps.community to pull back the curtain on how one of Europe…
Autonomous Agents at Work: From OpenClaw Hype to Enterprise Reality [not-audio_url] [/not-audio_url]

Duration: 42:19
Pramod Krishnan is a Managing Director - AI Managed Services at PwC, specializing in enterprise AI transformation — helping large organizations move from AI experimentation to production operating models. In this episode…
Agents are Just While Loops [not-audio_url] [/not-audio_url]

Duration: 41:11
Hamza Tahir, co-founder of ZenML, joins the show to cut through the hype around long-running agents — arguing that at the end of the day, an agent is just a while loop that talks to a model, calls a tool, and writes to a…
The Latency Goldilocks Zone Explained [not-audio_url] [/not-audio_url]

Duration: 48:13
Rafael (Head of Innovation, iFood) and Daniel (Data and AI Manager, iFood) pull back the curtain on ILO-Agent — iFood's conversational AI ordering system built for 200 million users across Latin America. Recorded live at…
Building MCP Before MCP Existed: Inside Despegar's Sofia Agent [not-audio_url] [/not-audio_url]

Duration: 41:13
Nicolas Alejandro Bogliolo is the AI PM at Despegar, the largest online travel agency in Latin America, and the engineer-product-hybrid behind Sofia, the GenAI travel concierge that beat most of the OTA world to a workin…
Voice Agent Use Cases [not-audio_url] [/not-audio_url]

Duration: 51:04
This episode is brought to you by the MLflow team. Check out more information at MLflow.org.What does it actually take to build voice AI at a billion-interaction scale? This episode features an ex-Amazon voice AI enginee…
It's 2026, and We're Still Talking Evals [not-audio_url] [/not-audio_url]

Duration: 40:56
Maggie Konstanty is an AI Product Manager at Prosus, one of the world's largest consumer internet companies, where she builds and evaluates AI agents for food ordering and ecommerce at scale. She's been inside the messy…
Why Agents are Driving Software Development to the Cloud [not-audio_url] [/not-audio_url]

Duration: 51:07
This episode is brought to you by Hyperbolic and the MLflow team. Check out more information at hyperbolic.ai and MLflow.org.Why AI Coding Agents Are Moving to the Cloud — With Zach Lloyd, CEO of WarpZach Lloyd is the fo…
The Modern Software Engineer [not-audio_url] [/not-audio_url]

Duration: 53:37
This episode is brought to you by the MLflow team. Check out more information at MLflow.org.Mihail Eric is Head of AI at Monaco and Adjunct Lecturer at Stanford University, where he teaches CS146S: "The Modern Software D…