back

Are MCPs Overhyped? A Rant about MCPs

Why multi-cloud platforms might disappoint

In today's tech landscape, multi-cloud platforms (MCPs) have emerged as the supposed silver bullet for organizations looking to harness the power of multiple cloud providers while avoiding vendor lock-in. Yet beneath the glossy marketing and ambitious promises lies a more nuanced reality that many enterprises are only discovering after significant investment. As Henry Mao of Smithery argues in his recent presentation, MCPs might be solving the wrong problems while creating new ones along the way.

The core challenge with multi-cloud platforms

Henry Mao's presentation cuts through the hype surrounding multi-cloud platforms with several thought-provoking arguments:

  • MCPs don't truly solve vendor lock-in – While they promise freedom from dependence on a single cloud provider, they actually create a new form of lock-in to the MCP itself, which often comes with its own proprietary abstractions and limitations.

  • The abstraction tax is substantial – By creating a layer that works across multiple cloud environments, MCPs inevitably sacrifice native cloud capabilities, performance optimizations, and introduce additional complexity that requires specialized expertise.

  • Focus shifts from business value to infrastructure – Organizations adopting MCPs often find themselves dedicating significant resources to managing the platform itself rather than delivering actual business value through their applications.

  • Cost savings rarely materialize – Despite promises of optimizing costs across providers, the reality is that the additional complexity, specialized skills required, and abstraction overhead frequently outweigh any theoretical savings.

Why this matters: The hidden consequences of abstraction

The most insightful takeaway from Mao's analysis is how MCPs fundamentally misunderstand the core challenges of modern cloud development. Rather than enabling teams to work more efficiently, they often introduce what he calls an "abstraction tax" that compounds over time, creating technical debt that becomes increasingly difficult to manage.

This matters tremendously because we're at an inflection point in enterprise IT strategy. With cloud spending continuing to accelerate—Gartner forecasts worldwide public cloud spending to grow 20.7% to $591.8 billion in 2023—organizations are making decisive architecture choices that will impact their operations for years to come. The wrong abstraction doesn't just impact engineering efficiency; it creates strategic limitations that can hinder business agility and innovation at

Recent Videos

May 6, 2026

Hermes Agent Master Class

https://www.youtube.com/watch?v=R3YOGfTBcQg Welcome to the Hermes Agent Master Class — an 11-episode series taking you from zero to fully leveraging every feature of Nous Research's open-source agent. In this first episode, we install Hermes from scratch on a brand new machine with no prior skills or memory, walk through full configuration with OpenRouter, tour the most important CLI and slash commands, and run our first real task: a competitor research report on a custom children's book AI business idea. Every future episode will build on this fresh install so you can see the compounding value of the agent in real time....

Apr 29, 2026

Andrej Karpathy – Outsource your thinking, but you can’t outsource your understanding

https://www.youtube.com/watch?v=96jN2OCOfLs Here's what Andrej Karpathy just figured out that everyone else is still dancing around: we're not in an era of "better models." We're in a different era of computing altogether. And the difference between understanding that and not understanding it is the difference between being a vibe coder and being an agentic engineer. Last October, Karpathy had a realization. AI didn't stop being ChatGPT-adjacent. It fundamentally shifted. Agentic coherent workflows started to actually work. And he's spent the last three months living in side projects, VB coding, exploring what's actually possible. What he found is a framework that explains...

Mar 30, 2026

Andrej Karpathy on the Decade of Agents, the Limits of RL, and Why Education Is His Next Mission

A summary of key takeaways from Andrej Karpathy's conversation with Dwarkesh Patel In a wide-ranging conversation with Dwarkesh Patel, Andrej Karpathy — former head of AI at Tesla, founding member of OpenAI, and creator of some of the most popular AI educational content on the internet — shared his views on where AI is headed, what's still broken, and why he's now pouring his energy into education. Here are the key takeaways. "It's the Decade of Agents, Not the Year of Agents" Karpathy's now-famous quote is a direct pushback on industry hype. Early agents like Claude Code and Codex are...