Ipybox

io.github.gradion-aiPublished by GitHub account gradion-aiv0.9.2Updated Oct 24, 2026

Unified execution environment for Python code, shell commands, and programmatic MCP tool calls

VerifiedSTDIODesktop onlyDeveloper Tools AI & ML

Server details

Identifier: io.github.gradion-ai/ipybox
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

The registry verified the GitHub account gradion-ai for this listing. That does not show the account is the product's maker.

SourceWeft's checks cover whether the listing is complete and the endpoint answered; they do not review the server's code or what its tools do.

Add a badge to your README

Show readers this MCP server is listed on SourceWeft. The badge links to this page.

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.gradion-ai%2Fipybox.svg)](https://sourceweft.com/mcp/io.github.gradion-ai%2Fipybox?utm_source=readme&utm_medium=badge)

Overview

AI-generated overview

Runs Python code, shell commands, and MCP tool calls in a stateful local IPython kernel.

What you can do: Ipybox provides a unified execution environment where a single code block can mix Python code, shell commands, and programmatic MCP tool calls. State persists across executions in an IPython kernel, and shell output can be captured into Python variables. It generates typed Python APIs and Pydantic models from MCP tool schemas, and supports application-level approval of individual tool calls and shell commands. Kernels can optionally be sandboxed with sandbox-runtime for filesystem and network restrictions.
When to use it: Useful when an assistant needs to run multi-step Python or shell work with persistent state, or to call MCP tools through generated Python APIs instead of raw JSON. It suits local workflows that need protected access to local data and tools, and can be added as an MCP server for code actions and programmatic tool calling.
Requirements: Runs locally as a stdio process, installed from PyPI as ipybox and started with uvx. No authentication, environment variables, or headers are declared. Optional sandboxing uses sandbox-runtime. Desktop only; no web executable.

Before you install

It executes arbitrary Python code and shell commands on the user's machine, so code and commands should be reviewed before running. Application-level approval of individual tool calls and shell commands is available and worth enabling. Sandboxing is optional, not automatic, so filesystem and network restrictions apply only when configured.

Installation

In SourceWeft

Open Ipybox in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

[ipybox]

ipybox

mcp-name: io.github.gradion-ai/ipybox

[Website] [PyPI - Version] [GitHub Release] [GitHub Actions Workflow Status] [GitHub License]

ipybox is a unified execution environment for Python code, shell commands, and programmatic MCP tool calls.

Overview

ipybox executes code blocks in a stateful IPython kernel. A code block can contain any combination of Python code, shell commands, and programmatic MCP tool calls. Kernels can be sandboxed with sandbox-runtime, enforcing filesystem and network restrictions at OS level.

It generates Python APIs for MCP server tools via mcpygen, and supports application-level approval of individual tool calls and shell commands during code execution. ipybox runs locally on your computer, enabling protected access to your local data and tools.

[!NOTE] Next generation ipybox

This is the next generation of ipybox, a complete rewrite. Older versions are maintained on the 0.6.x branch and can be obtained with pip install ipybox<0.7.

Documentation:

Capabilities

Capability	Description
Stateful execution	State persists across executions in IPython kernels
Unified execution	Combine Python code, shell commands, and programmatic MCP tool calls in a code block
Shell command execution	Run shell commands via `!cmd` syntax, capture output into Python variables
Programmatic MCP tool calls	MCP tools called via generated Python API ("code mode"), not JSON directly
Python tool API generation	Typed functions and Pydantic models generated from MCP tool schemas via mcpygen
Application-level approval	Individual approval of tool calls and shell commands during code execution
Lightweight sandboxing	Optional kernel isolation via Anthropic's sandbox-runtime
Local execution	No cloud dependencies, everything runs locally on your machine

Usage

Component	Description
Python SDK	Python API for building applications on ipybox
MCP server	ipybox as MCP server for code actions and programmatic tool calling
Claude Code plugin	Plugin that bundles the ipybox MCP server and a code action skill

[!TIP] Freeact agent

Freeact is a general-purpose agent built on ipybox.

Source: README.md at commit 264ed6c

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v0.9.2LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
License10 pts