CodeMode & Recently Updated Servers: Remote MCP Updates

How code generation is replacing multi-step tool calling, and tracking the latest MCP servers on Remote-MCP.com

Hey everyone, it’s been a while since the last post due to a busy period for me personally. It’s also been a busy period for Remote MCP - since the last post there has been CodeMode, ChatGPT Apps, and the Official Registry. Here’s our view on CodeMode.

We’re also excited to release a new page to our website: Recently Updated. The Recently Updated page is powered by the Official Registry, so everyone can keep up-to-date with new Remote MCP Servers. The page only includes Remote MCP Servers that have been submitted to the registry - if you think any are worthy of inclusion on our main list, then please submit a PR to add the server.

Let’s kick on

CodeMode

A new paradigm for LLM tool use. CodeMode is based on the idea that models are very good at generating code, but not quite there with multi-step tool calling. To solve this, CodeMode swaps the ask - replacing tool calling with code generation. The early results appear to be the holy grail: higher performance, with lower token use.

So how does this work?

Simply put, rather than exposing N tools to a model, you expose a single tool:

CodeMode

Description: A tool that can generate code to achieve a goal
Input type: {“functionDescription”: string }
Output type: {“result” string }

The CodeMode tool generates code, executes, and returns the result as the tool output. This reduces multi-step tool calls into a single (albeit complex) step. How does this work?

The trick is to expose the N tools as a library, with each tool corresponding to a library function. Then we find:

• The tool input precisely defines the arguments of the tool function, fully typed

• The tool output defines the return type of the function

• The tool description acts as documentation on how and why to use the function.

Now when a model generates the code to achieve the task, it can use each tool just like it was a built-in function. When executing the generated code, the tools are invoked directly by the generated library code. This means for a Remote MCP server, during the code generation step, the server’s tools are available as a full library.

There are a lot of parts to creating this setup in production - with sandboxing the code execution being critical. The Cloudflare blog post goes into more detail, and is a very good read on the topic using dynamic worker loaders - a sandboxing primitive which is worth a deep dive of its own.

Recently Updated Remote MCP Servers

Make sure to keep track of new and and updated servers on our new page!