The next generation of MCP

Over the last year and a half, the Model Context Protocol (MCP) has become the universal standard for how agents interact with external services. 

But one of the main criticisms of MCP was that the protocol required a stateful connection between Client and Server. This evolved from MCP’s origins and the first STDIO transport, designed for local applications. When MCP Servers went remote, it translated the stateful connection that worked so well locally and transposed it onto web infrastructure. Building a well-behaved MCP Server meant managing request routing to sticky sessions, holding open streams, message replay, and generally more overhead and complexity than a traditional web server. This changes now.

The latest MCP 2026-07-28 specification was released last week, together with updated TypeScript, Python, Go, and C# SDKs. MCP is now a fully stateless protocol. The specification, interaction model and SDKs have all been rewritten to leverage this new protocol and simplify usage. This means that MCP servers can now run in just a Worker, no stateful infrastructure needed, and customers benefit from the operational simplicity and reduced cost of less moving parts. 

A new MCP

At Cloudflare, our journey with MCP goes back to the very beginning. Continue reading

Your agent needs a computer, not a container — introducing @cloudflare/computer

The most capable agents have something simple in common: they are given their own computer to work with.

Coding agents work this way. You give them a filesystem, a shell, tools, packages, and the ability to run code. They inspect the environment, make changes, test their work, and keep going. The computer gives the model a familiar way to act on the world. At Cloudflare, we’re working hard to provide the right primitives on which to build the most capable agents.

Today we’re introducing an early preview of @cloudflare/computer. The @cloudflare/computer package provides an agent runtime where the details and mechanics of what code runs in an isolate, a container sandbox, or a web browser are handled by the platform. Each agent gets a computer, the runtime optimizes for efficiency, and scalability.

We believe that in order to meet the growing demand for compute required by agentic systems we need to look to solutions beyond traditional containerization. 

Changing how agents are built

We’ve seen a subtle evolution of this story over the past six months. At the start of the year, spinning up a container and running an agent inside of it was the norm. In recent months, we’ve Continue reading

Code Mode: give agents an entire API in 1,000 tokens

Model Context Protocol (MCP) has become the standard way for AI agents to use external tools. But there is a tension at its core: agents need many tools to do useful work, yet every tool added fills the model's context window, leaving less room for the actual task.

Code Mode is a technique we first introduced for reducing context window usage during agent tool use. Instead of describing every operation as a separate tool, let the model write code against a typed SDK and execute the code safely in a Dynamic Worker Loader. The code acts as a compact plan. The model can explore tool operations, compose multiple calls, and return just the data it needs. Anthropic independently explored the same pattern in their Code Execution with MCP post.

Today we are introducing a new MCP server for the entire Cloudflare API — from DNS and Zero Trust to Workers and R2 — that uses Code Mode. With just two tools, search() and execute(), the server is able to provide access to the entire Cloudflare API over MCP, while consuming only around 1,000 tokens. The footprint stays fixed, no matter how many API endpoints exist.

For a large API like Continue reading