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With a stateless makeover, new MCP spec targets enterprise scale

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Why This Matters

The new MCP specification's stateless design and extended deprecation policy aim to facilitate easier deployment at enterprise scale, marking a significant evolution from its original local machine focus. Supported by major industry players and managed by the Linux Foundation, this update enhances stability and longevity for enterprise AI integrations, signaling a move toward more scalable and reliable AI infrastructure.

Key Takeaways

The hope is that the changes, detailed in the protocol’s documentation, will make widespread deployment in an enterprise context much easier. MCP started as something that simply ran on a local machine, connecting models to local apps, so the new spec is a major rethink of some of its foundations.

There is also a new deprecation policy that ensures at least 12 months between when a feature’s formal deprecation is enacted and when the feature may actually be removed—with a narrow exception for critical security updates. This is again in keeping with the general “let’s make this work better at enterprise scale” theme of the new specification.

MCP is managed by the Agentic AI Foundation (AAIF), which sits under the Linux Foundation. MCP was originally introduced by Anthropic, just shy of two years ago, and Anthropic still has significant influence over its direction. Nonetheless, it has grown beyond just Anthropic—OpenAI, Google, Microsoft, and Amazon also contribute to it—and it’s supported by many developer tools and, increasingly, a wide range of software and services used for other knowledge and creative work.

The buck technically stops with individual maintainers, not any of these companies themselves, but as noted above, some of the principle maintainers currently work at Anthropic.