Server-Side Code Execution Tools for AI Agents, Compared

Say you’re building an agent that answers questions about a CSV a customer uploaded. The model needs to run Python to get the answer. Where does that code run? One option is to run it yourself. That means a sandbox platform such as E2B or Modal, or your own container on Docker, plus the work of keeping it away from your database and the internet, capping its runtime, and patching the image. A server-side code execution tool is the other option. You add the tool to your API request, the model decides when it needs to run something, and the provider runs the commands in its own sandbox and returns the output to the model inside the same request. A sandbox here means an isolated Linux container with its own filesystem, a time limit, and no network access by default. This article covers four providers that offer server-side code execution today, what each sandbox can and can’t do, what it costs in latency and money, and the jobs that still need a sandbox you operate yourself. A server-side code execution tool runs the model’s commands in the provider’s sandbox during your API request. You don’t provision, patch, or secure a…