"A sandbox for executing Python code" matching MCP servers:

自托管的MCP服务器，在Docker沙箱中提供命令执行、后台长任务、大文件传输和多沙箱自动管理，专为AI助手设计。

A Python MCP server that generates complete Vue 3 CRUD structures with Composition API, including components, services, stores, and routes.

Enables LLMs to interact with Python environments, execute code, manage files, and handle packages through the Model Context Protocol.

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

MCP server providing AI agents with persistent shells, filesystem access, and multi-machine management backed by Docker containers or remote SSH hosts.

Enables LLMs to run Python code and scripts across system and conda environments, list and install packages, and read or write text and binary files within an isolated working directory. It also provides prompt templates for generating, refactoring, and debugging Python code.

Enables LLMs to manage Python environments, execute Python code and scripts, install packages, and read or write files securely within a configured working directory.

Enables LLMs to manage Python environments, execute code and scripts, install packages, and read or write files within an isolated working directory.

Enables LLMs to interact with Python environments, run code and scripts, manage packages, and read or write files within a configured working directory.

Enables LLMs to execute Python code and scripts, manage Python environments and packages, and read or write files within an isolated working directory. It also provides prompt templates for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to interact with local Python environments, execute code and scripts, manage packages, and read or write files within an isolated working directory.

Enables LLMs to run Python code and scripts, manage Python environments and packages, and read or write files within an isolated working directory. It also provides prompts for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to interact with Python environments, execute code and scripts, manage packages, and read or write files within an isolated working directory.

Enables LLMs to interact with Python environments, execute code or scripts, manage packages, and read/write files within an isolated working directory.

Enables LLMs to execute Python code and scripts across system and conda environments, manage installed packages, and read or write text and binary files within an isolated working directory.

Enables LLMs to work with local Python environments by listing environments and installed packages, installing dependencies, and running code or scripts. Also supports reading, writing, and listing files within a sandboxed working directory.

Enables LLMs to manage Python environments and packages, execute Python code or scripts, and read or write files within a secured working directory. It also provides prompts for common Python tasks such as function creation, refactoring, and debugging.

Enables LLMs to interact with Python environments, execute code, manage packages, and perform file operations within a configurable working directory.

Provides an AI agent with authenticated shell and file access to a sandbox host, plus a restricted gateway for safe deploys on a production host via forced SSH commands.

Enables LLMs to run Python code and scripts across available environments, manage packages, and read/write files within a secured working directory. It also provides prompts and resources for common Python development tasks.