ipybox

ipybox is a lightweight and secure Python code execution sandbox based on IPython and Docker. You can run it locally on your computer or remotely in an environment of your choice. ipybox is designed for AI agents that need to execute code safely e.g. for data analytics use cases or executing code actions like in freeact agents.

Features

Secure code execution inside Docker containers
Restrict network access with a configurable firewall
Stateful code execution with IPython kernels
Stream code execution output as it is generated
Install Python packages at build time or runtime
Return plots generated with visualization libraries
Exposes an MCP server interface for AI agent integration
Invocation of MCP servers via generated client code
Flexible deployment options, local or remote
asyncio API for managing the execution environment

Documentation

MCP server

ipybox can be installed as MCP server.

{
  "mcpServers": {
    "ipybox": {
      "command": "uvx",
      "args": ["ipybox", "mcp"]
    }
  }
}

Python example

Install ipybox Python package:

pip install ipybox

Execute code in an ipybox container:

import asyncio
from ipybox import ExecutionClient, ExecutionContainer

async def main():
    async with ExecutionContainer(tag="ghcr.io/gradion-ai/ipybox") as container:
        async with ExecutionClient(port=container.executor_port) as client:
            result = await client.execute("print('Hello, world!')")
            print(f"Output: {result.text}")

if __name__ == "__main__":
    asyncio.run(main())

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A Python code execution sandbox based on IPython and Docker. Stateful code execution, file transfer between host and container, configurable network access.

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ipybox

ipybox

Features

Documentation

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Python example

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