"How to run a Python script in a sandboxed environment" matching MCP servers:

Enables AI assistants to manage OpenStack cloud resources including compute, images, identity, network, and block storage via the Model Context Protocol.

An interactive Python code execution environment that allows users and LLMs to safely execute Python code and install packages in isolated Docker containers.

A VMware ESXi/vCenter management server based on MCP (Machine Control Protocol), providing simple REST API interfaces for virtual machine management.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

AI-powered cloud development IDE, so you can run AI to surf in a secure sandbox environment.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.

Run AI agents in VM-isolated sandboxes on your Mac.

Enables AI assistants to run Kali Linux security tools in an isolated Docker container for tasks like network scanning, port checking, and service enumeration.

Enables running arbitrary JavaScript code in isolated Docker containers with on-demand npm dependency installation, allowing for ephemeral script execution and long-running services with controlled resource limits.

An MCP server that enables AI assistants to manage Docker containers, images, networks, and volumes through a standardized interface. It supports comprehensive operations like container lifecycle management and image pulling while ensuring correct handling of command and environment variable arrays.

Enables AI agents to spin up disposable Tenki microVM sandboxes in seconds and use them to run code, manage files, run git commands, and expose preview URLs.

A Model Context Protocol server that enables AI clients to interact with virtual Ubuntu desktops, allowing them to browse the web, run code, and control instances through mouse/keyboard actions and bash commands.

A Model Context Protocol (MCP) server for Proxmox Virtual Environment that enables AI assistants to manage virtual machines, containers, nodes, and resources through natural language interactions.

An MCP server that enables interaction with development containers through the devcontainers CLI, allowing users to start, run commands in, and execute arbitrary shell commands inside devcontainers.

Create sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.

An MCP server that provides AI agents with a full Ubuntu desktop environment inside Docker, enabling them to perform complex computer tasks like browsing, coding, testing, and GUI automation.

Enables AI assistants to manage Docker containers, images, volumes, networks, and compose projects through Arcane's API. Provides comprehensive tools for environment, container, image, volume, network, project, and system operations.

A template MCP server that provides a basic structure and configuration for building Model Context Protocol servers. Includes Docker support, environment configuration, and examples for both STDIO and SSE transport modes.

A Python MCP server for Proxmox VE that lets AI agents read cluster status, power guests on/off, and provision new VMs/containers through natural language, while preventing any destructive actions.