New MCP specification released to standardise AI integration
The new MCP 2026-07-28 specification has been released. The update introduces a transition to a stateless architecture and strengthened authorisation requirements for AI integrations.

What happened?
On 28 July 2026, the new MCP 2026-07-28 specification for the Model Context Protocol (MCP) was released. The update marks a transition to a stateless architecture, introduces standardised protocol extensions, and imposes higher requirements for authorisation and authentication when connecting AI systems with external tools.
Key facts
| Lanseringsdatum | 28 juli 2026 |
|---|---|
| Specifikationsversion | MCP 2026-07-28 |
| Månatliga SDK-nedladdningar | Över 400 miljoner |
| Tillväxt under 2026 | Fyrfaldig ökning |
Why it matters
This is described as the most comprehensive revision of MCP since the protocol's inception. The shift to a stateless architecture reduces complexity when scaling, while the standardised extensions and strengthened security protocols facilitate more secure and stable integration patterns as the use of AI agents grows globally.
Who is affected?
The update affects AI developers, system architects, and companies building or integrating AI agents with external applications and data sources. The changes make it easier to scale AI integrations in enterprise environments requiring higher performance and security.
Impact on the EU
The specification is a global open standard and was made available to developers worldwide upon its release on 28 July 2026. Because the protocol focuses on technical interfaces and security authorisation, the strengthened authentication mechanisms facilitate compliance with European data security requirements for AI integrations.
What else you should know
The Model Context Protocol was originally launched by Anthropic in 2024 to provide a unified way for AI models to communicate with databases and tools. Adoption has grown rapidly in the industry, with the protocol's SDK now recording over 400 million downloads per month.
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- Assess technical risk: model choice, vendor lock-in, data flow and running cost.
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