Model Context Protocol prepares to break with its stateful past

Summary

AI seemed simpler in 2024 when Anthropic released the first version of the Model Context Protocol (MCP), an open standard for connecting AI applications to external systems.Back then, developers primarily used the protocol on their personal computers. As those laptop-bound demos were adapted for multi-client enterprise use, MCP servers moved into the cloud, where the original design quickly created scalability problems.On July 28, MCP's maintainers plan to finalize the protocol's 2026-07-28 revision, bringing many changes – including some that aren't backward compatible – that reflect some "hard lessons" the core MCP team learned over the past two years, said Anthropic technical staff member David Soria Parra in a livestream Tuesday. The 2026-07-28 revision will come with the "most substantial changes we have made to the specification, probably since adding authorization," Parra said. "A lot of things that made MCP are gone." Parra claims the new MCP will be easier to deploy and use. If users have been updating their SDKs, they shouldn't have much problem upgrading.But he also warned that the underlying data transfer mechanism has totally been rebuilt, which "makes things on the wire a bit more complicated than they used to be." Protocol-level session tracking will no longer be required.For those who rolled their own MCP engine, some long days of reconfiguration may be ahead. "If you built your own implementation, it's going to be a lot of uplift to make this correct," Parra admitted. Anthropic donated MCP in 2025 to the AAIF, a Linux Foundation fund co-founded by Anthropic, Block, and OpenAI. By that time, the SDK was being downloaded over 97 million times a month and at least 10,000 MCP servers had been set up.MCP is now stateless like the rest of the internetThe chief change is that the new revision removes protocol-level sessions, allowing each request to be handled independently. This "stateless" approach, common in the cloud-native world, is used to scale web ...