jupyter-mcp-sandboxes 0.1.0

Sandboxes extension for Jupyter MCP Server (launch/use code-sandboxes runtimes as an alternative to Jupyter kernels)

🪐🔧 Jupyter MCP Server Sandboxes Extension

jupyter_mcp_sandboxes is an optional extension for jupyter-mcp-server that adds sandbox-backed code execution. It is discovered automatically through the jupyter_mcp_server.extensions entry point (powered by reactor) once installed.

Features

Installing this extension exposes four additional MCP tools:

• launch_sandbox — launch a sandbox runtime (eval, docker, jupyter, datalayer, colab, kaggle, monty, modal).
• list_sandboxes — list launched sandboxes and their state.
• use_sandbox — select (or clear) the active sandbox used by execute_code.
• terminate_sandbox — stop and unregister a sandbox.

It also lets SANDBOX_VARIANT route the standard notebook/cell execution tools through a non-jupyter backend via a SandboxKernel adapter.

Installation

pip install jupyter_mcp_sandboxes

Backend-specific extras are provided by the underlying code-sandboxes package, e.g.:

pip install "code-sandboxes[modal]"   # Modal
pip install "code-sandboxes[colab]"   # Google Colab
pip install "code-sandboxes[kaggle]"  # Kaggle

Usage

Once installed, start jupyter-mcp-server as usual — no flag is required. The sandbox tools appear automatically. To route execute_code through a specific backend by default, set SANDBOX_VARIANT:

SANDBOX_VARIANT=monty jupyter-mcp-server start --transport streamable-http

License

BSD 3-Clause License. Copyright (c) 2024- Datalayer, Inc.