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

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

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

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

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

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

MCP server that provides tools to access Google Maps Environment APIs for air quality, pollen, and weather data, enabling queries like current conditions, forecasts, and history.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

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.

Connects AI assistants to Swiss environmental data from BAFU, including air quality, hydrology, natural hazards, and open datasets, with no API keys required.

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 MCP-compatible AI agents to deploy and manage applications on Google Cloud Run, including service deployment, listing, logging, and project creation.

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

Enables AI coding assistants to browse Unreal Python API documentation, search classes and functions, and execute Python code in Unreal Editor.

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.

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.

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

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

Run Python, JavaScript, or shell snippets in secure, resource-limited Docker containers with no network access, exposed as MCP tools.