"A sandbox environment for running REPL code" matching MCP servers:

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

This server gives AI clients a persistent, isolated Linux container in which the model can run any bash command as root with internet access, install packages and start long-running processes without command filtering. Files produced inside it can be handed back to the user as signed, expiring public download links suitable for PDFs, images, audio and video.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables coding agents and users to share live tmux-based REPL sessions for many languages, allowing agents to execute code in the same interactive workspace via MCP.

Enables creation and management of persistent REPL sessions for various languages and shells, with web-based monitoring and session recovery capabilities.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

Async Python REPL + Shell execution for MCP. Provides persistent state, background jobs, interactive input() bridging, and crash isolation in a single server.

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.

一个基于MCP的Python REPL服务器，支持多会话管理、代码执行、历史记录回放和包安装，为AI提供Python解释器能力。

A sandbox MCP server for testing and debugging MCP tools and interactions via the MCP Inspector.

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.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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

Enables stateful subprocess sessions (REPLs) and tmux-backed TUI program control for interactive tools like Python, r2, or shells.

Enables MCP-compatible AI clients to run curated Kali Linux security tools such as nmap, gobuster, nikto, sqlmap and netcat inside an isolated microVM sandbox. Commands execute as asynchronous jobs with readable output, cancellation and persistent per-workspace storage, with configurable network, CPU and memory limits.

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

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.

Enables AI coding agents to work inside a disposable Windows guest desktop, where they can run shell commands, launch applications, inspect and operate native GUI controls, perform browser DOM actions, and transfer files. Fresh observations, PNG screenshots, and hashed artifacts let agents verify results without touching the host desktop.

Enables chat clients to execute real shell commands (apt install, curl, ffmpeg, Python) inside a disposable, per-conversation Debian container and hand resulting files back to the user via signed download links. Installed packages and processes are discarded when the container recycles, while files under /workspace persist.