"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.

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.

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

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 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.

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

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.

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 Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.