"How to execute a Python script" matching MCP servers:

Enables coding agents to execute Python code, run script files, and install pip packages locally via MCP.

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

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

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

An MCP server that exposes Python debugging tools backed by debugpy, providing a focused debugging surface for local scripts.

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.

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

Enables LLMs to interact with Python environments, execute code, manage files, and handle packages through the Model Context Protocol.

Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.

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

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

Enables users to create, manage, and execute Google Apps Script projects through natural language. It provides comprehensive tools for code editing, function execution, deployment management, and monitoring script processes.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

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.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

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

Provides a persistent Python REPL session as a tool for executing code, managing files, installing packages, and initializing projects via the MCP protocol.

Enables AI assistants to execute Python functions and system commands via Streamable HTTP, including bash, Python code execution, file operations, and text searching.

Executes Python code with safety constraints and manages Python packages through the Model Context Protocol.

Enables execution, listing, reading, and help retrieval of local Bash, PowerShell, and Python scripts from a specified directory.