| Name | ipybox JSON |
| Version |
0.6.6
JSON |
| download |
| home_page | None |
| Summary | Python code execution sandbox based on IPython and Docker |
| upload_time | 2025-09-14 09:57:45 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.11 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# ipybox
mcp-name: io.github.gradion-ai/ipybox
<p align="left">
<a href="https://gradion-ai.github.io/ipybox/"><img alt="Website" src="https://img.shields.io/website?url=https%3A%2F%2Fgradion-ai.github.io%2Fipybox%2F&up_message=online&down_message=offline&label=docs"></a>
<a href="https://pypi.org/project/ipybox/"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/ipybox?color=blue"></a>
<a href="https://github.com/gradion-ai/ipybox/releases"><img alt="GitHub Release" src="https://img.shields.io/github/v/release/gradion-ai/ipybox"></a>
<a href="https://github.com/gradion-ai/ipybox/actions"><img alt="GitHub Actions Workflow Status" src="https://img.shields.io/github/actions/workflow/status/gradion-ai/ipybox/test.yml"></a>
<a href="https://github.com/gradion-ai/ipybox/blob/main/LICENSE"><img alt="GitHub License" src="https://img.shields.io/github/license/gradion-ai/ipybox?color=blueviolet"></a>
<a href="https://pypi.org/project/ipybox/"><img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/ipybox"></a>
</p>
`ipybox` is a lightweight and secure Python code execution sandbox based on [IPython](https://ipython.org/) and [Docker](https://www.docker.com/). 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`](https://github.com/gradion-ai/freeact/) agents.
<a href="https://glama.ai/mcp/servers/@gradion-ai/ipybox">
<img width="380" height="200" src="https://glama.ai/mcp/servers/@gradion-ai/ipybox/badge" alt="ipybox MCP server" />
</a>
<p align="center">
<img src="docs/img/logo.png" alt="logo">
</p>
## Features
- Secure code execution inside Docker containers
- [Restrict network access](https://gradion-ai.github.io/ipybox/examples/#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](https://gradion-ai.github.io/ipybox/mcp-server/) interface for AI agent integration
- [Invocation of MCP servers](https://gradion-ai.github.io/ipybox/mcp-client/) via generated client code
- Flexible deployment options, local or remote
- `asyncio` API for managing the execution environment
## Documentation
- [User Guide](https://gradion-ai.github.io/ipybox/)
- [API Docs](https://gradion-ai.github.io/ipybox/api/execution_container/)
## MCP server
`ipybox` can be installed as [MCP server](https://gradion-ai.github.io/ipybox/mcp-server/).
```json
{
"mcpServers": {
"ipybox": {
"command": "uvx",
"args": ["ipybox", "mcp"]
}
}
}
```
## Python example
Install `ipybox` Python package:
```bash
pip install ipybox
```
Execute code in an `ipybox` container:
```python
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())
```
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"description": "# ipybox\n\nmcp-name: io.github.gradion-ai/ipybox\n\n<p align=\"left\">\n <a href=\"https://gradion-ai.github.io/ipybox/\"><img alt=\"Website\" src=\"https://img.shields.io/website?url=https%3A%2F%2Fgradion-ai.github.io%2Fipybox%2F&up_message=online&down_message=offline&label=docs\"></a>\n <a href=\"https://pypi.org/project/ipybox/\"><img alt=\"PyPI - Version\" src=\"https://img.shields.io/pypi/v/ipybox?color=blue\"></a>\n <a href=\"https://github.com/gradion-ai/ipybox/releases\"><img alt=\"GitHub Release\" src=\"https://img.shields.io/github/v/release/gradion-ai/ipybox\"></a>\n <a href=\"https://github.com/gradion-ai/ipybox/actions\"><img alt=\"GitHub Actions Workflow Status\" src=\"https://img.shields.io/github/actions/workflow/status/gradion-ai/ipybox/test.yml\"></a>\n <a href=\"https://github.com/gradion-ai/ipybox/blob/main/LICENSE\"><img alt=\"GitHub License\" src=\"https://img.shields.io/github/license/gradion-ai/ipybox?color=blueviolet\"></a>\n <a href=\"https://pypi.org/project/ipybox/\"><img alt=\"PyPI - Python Version\" src=\"https://img.shields.io/pypi/pyversions/ipybox\"></a>\n</p>\n\n`ipybox` is a lightweight and secure Python code execution sandbox based on [IPython](https://ipython.org/) and [Docker](https://www.docker.com/). 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`](https://github.com/gradion-ai/freeact/) agents.\n\n<a href=\"https://glama.ai/mcp/servers/@gradion-ai/ipybox\">\n <img width=\"380\" height=\"200\" src=\"https://glama.ai/mcp/servers/@gradion-ai/ipybox/badge\" alt=\"ipybox MCP server\" />\n</a>\n\n<p align=\"center\">\n <img src=\"docs/img/logo.png\" alt=\"logo\">\n</p>\n\n## Features\n\n- Secure code execution inside Docker containers\n- [Restrict network access](https://gradion-ai.github.io/ipybox/examples/#restrict-network-access) with a configurable firewall\n- Stateful code execution with IPython kernels\n- Stream code execution output as it is generated\n- Install Python packages at build time or runtime\n- Return plots generated with visualization libraries\n- Exposes an [MCP server](https://gradion-ai.github.io/ipybox/mcp-server/) interface for AI agent integration\n- [Invocation of MCP servers](https://gradion-ai.github.io/ipybox/mcp-client/) via generated client code\n- Flexible deployment options, local or remote\n- `asyncio` API for managing the execution environment\n\n## Documentation\n\n- [User Guide](https://gradion-ai.github.io/ipybox/)\n- [API Docs](https://gradion-ai.github.io/ipybox/api/execution_container/)\n\n## MCP server\n\n`ipybox` can be installed as [MCP server](https://gradion-ai.github.io/ipybox/mcp-server/).\n\n```json\n{\n \"mcpServers\": {\n \"ipybox\": {\n \"command\": \"uvx\",\n \"args\": [\"ipybox\", \"mcp\"]\n }\n }\n}\n```\n\n## Python example\n\nInstall `ipybox` Python package:\n\n```bash\npip install ipybox\n```\n\nExecute code in an `ipybox` container:\n\n```python\nimport asyncio\nfrom ipybox import ExecutionClient, ExecutionContainer\n\nasync def main():\n async with ExecutionContainer(tag=\"ghcr.io/gradion-ai/ipybox\") as container:\n async with ExecutionClient(port=container.executor_port) as client:\n result = await client.execute(\"print('Hello, world!')\")\n print(f\"Output: {result.text}\")\n\nif __name__ == \"__main__\":\n asyncio.run(main())\n```\n",
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