With a stateless makeover, new MCP spec targets enterprise scale

This week, the Model Context Protocol (MCP), an open source standard for how AI systems interact with external tools and data sources, saw its largest update since its introduction. Most notably, MCP’s protocol core is now stateless, so requests are no longer dependent on a session tied to an individual server instance. This change has the potential to address long-standing barriers to scalability.

The blog post announcing the specification, written by lead maintainers David Soria Parra and Den Delimarsky (who both work at Anthropic), says:

The highlight of this release is a stateless protocol core—MCP is transforming from a bidirectional stateful protocol into a request/response stateless protocol. It was one of the most highly-requested features from developers who were eager to get better reliability and scalability for their MCP servers.

This update is “MCP’s most important since remote MCP first launched over a year ago,” Soria Parra also wrote. In addition, the update adds “Multi Round-Trip Requests, header-based routing, cacheable list results, authorization hardening, a formal extensions framework, and updated Tier 1 SDKs.”

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 principal maintainers currently work at Anthropic.