"How to run a Python script in a sandboxed environment" matching MCP servers:

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Enables LLMs to execute Python code securely in a sandboxed environment. Supports configurable restrictions like no network access and returns results including files.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Model Context Protocol server to run Python code in a sandbox.

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

A cognitive scripting language for structured reasoning with LLMs. 12 built-in operations (survey, ground, assert, doubt, contrast, synthesize, etc.) for guiding AI through dialectical analysis, impact assessment, and other thinking patterns.

Enables you to audit your AI agent skills by running each one against an agent that cannot see it, diffing the resulting artifacts, and grading whether each skill genuinely improves, changes nothing, or worsens the output.

Enables execution of arbitrary CLI tools and shell scripts by defining them in YAML configuration files as MCP Tools. Supports custom shells (bash, Python, Node.js, Deno), input parameters passed as environment variables, and flexible timeout settings.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

An MCP server that lets Claude read and push Google Apps Script code directly into a script project.

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

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

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

A server that provides a persistent Python REPL environment through the MCP protocol, allowing execution of Python code, variable management, and package installation.

Exposes your project's package.json scripts as MCP tools, allowing AI assistants to discover and execute npm/yarn/pnpm/bun scripts directly. Automatically detects your package manager and enables running scripts with optional arguments through natural language commands.

Processes test scenarios from user prompts to generate complete WDIO test suites with intelligent file management that analyzes existing files to determine whether to update them or create new ones.