"Information about sandbox environments or games" matching MCP servers:

Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

Enables AI coding agents to safely execute code, run tests, and build projects inside disposable Docker sandboxes, protecting the host machine through enforced isolation, filesystem snapshots, and network controls.

Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.

This MCP server enables MCP clients such as Claude Desktop to run LLM-generated code in a secure, isolated sandbox across multiple container backends and programming languages.

Enables agents to provision isolated Kubernetes runtimes where they can write files, run commands, start long-lived processes, and publish apps at authenticated URLs, all backed by per-user durable storage that outlives any runtime.

Enables AI agents to create isolated Docker runtimes, execute commands, manage workspace files, drive a headed browser, and retrieve artifacts through eight semantic MCP tools, with progressive capability discovery and explicit sandbox lifecycle.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Enables MCP-capable agents to execute generated Python, Node.js, or shell code inside disposable, network-isolated Docker containers with strict resource, filesystem, privilege, and time limits, returning structured results and errors.

Production-ready MCP server for secure Python code execution with artifact capture, virtual environment support, and LM Studio integration.

Execute scientific scripts (R, Python, GMT, LaTeX, Octave, Julia, etc.) in isolated, disposable containers with no host filesystem access.

A Model Context Protocol (MCP) server that enables LLMs to run ANY code safely in isolated Docker containers.

Enables AI agents to create, manage, and execute code in isolated Firecracker microVM sandboxes via the MCP protocol, with support for sandbox lifecycle and file operations.

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。

Spins up isolated opencode instances in Docker containers as MCP servers, providing 80 tools for file and shell operations within a scoped workspace without exposing the host filesystem.

Automatically converts JavaScript modules into MCP-compatible servers, making any JavaScript function accessible to AI systems through secure sandboxing with automatic type inference.

Enables AI clients to manage and execute development commands within isolated Railway sandboxes, providing a remote shell, file read/write, and sandbox lifecycle management for running tests, builds, and repository operations.

Provides isolated Docker environments for code execution, enabling users to create and manage containers, execute multi-language code, save and reproduce development environments, ensuring security and isolation.

Enables secure execution of bash, Python, and Node.js code in isolated Firecracker microVMs with configurable timeouts and no network access.

An extensible Message Communication Protocol server that provides secure code execution capabilities in isolated sandbox environments, compatible with Claude for Desktop and other MCP clients.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

Enables running Python and commands inside isolated, persistent Wasmer sandboxes on the host, while also exposing an Edge-deployed Postgres-backed service for storing notes and collecting feedback.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.

MCP server for E2B code sandbox, enabling creation, management, and execution of code in secure sandboxes using Python and shell commands.

Enables AI coding agents to run Kubernetes inspection and Terraform plan/apply operations inside ephemeral gVisor-sandboxed jobs with short-lived, narrowly-scoped credentials, while routing destructive changes through a human approval gate.

A Docker-based MCP server that enables AI to securely run Foundry test commands in isolated containers, with automatic dependency management and cleanup.

MCP server connecting Claude Code with E2B cloud sandboxes for working on any GitHub repo.

Creates short-lived, offline JavaScript sandbox containers for safe code execution via MCP, with no network access and strict resource limits.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug