"A sandbox environment to run Python code and install dependencies" matching MCP servers:

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

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

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.

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

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.

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.

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 running arbitrary JavaScript code in isolated Docker containers with on-the-fly npm dependency installation, supporting both ephemeral one-shot executions and persistent sandbox environments.

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

A Model Context Protocol server that enables AI assistants to create, control, and interact with virtual desktop environments through E2B's secure cloud sandboxes.

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

Provides ChatGPT with a persistent, VM-like Linux engineering workstation inside Docker, with root access, development tools, and a private nested Docker daemon.

A secure Docker-based environment that allows AI assistants to safely execute code without direct access to the host system by running all code within isolated containers.

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.

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

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

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.

Enables AI agents to safely test and debug PowerShell, CMD/BAT scripts, and system utilities inside isolated Hyper-V virtual machines, with snapshot rollback, host-to-guest file transfer, PowerShell Direct execution, and autonomous self-correction on failures.