Code Mode
AI agents run code in a sandbox. This helps them use tools better and saves money.
AI agents run code in a sandbox. This helps them use tools better and saves money.
Code Mode is an open-source library. It lets AI agents write and run their own code. This helps them interact with many tools easily. It creates a better way for agents to handle tasks. This can save a lot of money on token use.
Code Generation & Execution.
Agents write TypeScript or Python code. This code then runs in isolated sandboxes. It's a direct way for AI to act.
Automatic API Generation.
MCP tools turn into typed language interfaces. This happens automatically. These interfaces even come with documentation.
Secure Sandboxing.
Code runs in safe, isolated virtual environments. There is controlled access to resources. Importantly, there's no direct access to the computer's file system.
Context Efficiency.
This system uses far fewer tokens. It can reduce token usage by 90-98%. This is a huge saving compared to old tool-calling methods.
State Persistence.
It keeps track of information across different actions. This means it remembers things from one step to the next. This helps with complex tasks.
MCP Integration.
It works smoothly with over 230 existing MCP servers. There's good interaction with current systems.
No. Code Mode enhances MCP by giving you a better way to use MCP servers. It's a usage pattern that complements traditional MCP tool calling.
The code runs in Deno sandboxes. This means it can't access your computer's files or connect to just any network. Only the controlled MCP server connections are available.
Models that are really good at writing code work best, like the GPT-4 series, Claude 3 series, and Google Gemini. You don't need any special training for them.
The proxy itself adds very little delay, just milliseconds. The real boost in performance comes from not having to go back and forth multiple times with the LLM.
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