"Using Python REPL from an MCP server on Windows" matching MCP servers:

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.

一个基于MCP的Python REPL服务器，支持多会话管理、代码执行、历史记录回放和包安装，为AI提供Python解释器能力。

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

Enables coding agents and users to share live tmux-based REPL sessions for many languages, allowing agents to execute code in the same interactive workspace via MCP.

Enables creation and management of persistent REPL sessions for various languages and shells, with web-based monitoring and session recovery capabilities.

Async Python REPL + Shell execution for MCP. Provides persistent state, background jobs, interactive input() bridging, and crash isolation in a single server.

Enables MCP-compatible coding agents to schedule, check, postpone, and cancel Windows host shutdowns from WSL.

Enables stateful subprocess sessions (REPLs) and tmux-backed TUI program control for interactive tools like Python, r2, or shells.

Provides interactive Python REPL capabilities with persistent sessions, virtual environment support, package management via uv, and development tools like testing, linting, and code formatting for Python projects.

A lightweight server that enables AI agents to interact natively with the Windows operating system for tasks like UI automation and application control. It allows LLMs to perform file navigation, simulate user input, and manage windows without requiring specialized computer vision models.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

Enables launching and controlling real, visible Windows Telnet windows by reading their screen buffers and sending keyboard events, with session management and text-waiting capabilities.

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

Enables AI coding agents to work inside a disposable Windows guest desktop, where they can run shell commands, launch applications, inspect and operate native GUI controls, perform browser DOM actions, and transfer files. Fresh observations, PNG screenshots, and hashed artifacts let agents verify results without touching the host desktop.

Provides comprehensive Windows system control including file operations, process management, window control, screenshots, clipboard access, PowerShell/CMD execution, and optional mouse/keyboard automation and browser control capabilities.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables AI assistants to find and launch Windows applications by name using multi-strategy discovery via registry, Start Menu, PATH, and common directories.

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

Enables Claude to fully control a Windows desktop with native screen capture, low-level input injection, game-grade input, and play-testing capabilities.

A lightweight Windows automation MCP server that scopes UI operations to a single target window, offering tools like ReadWindow, PeekWindow, Click, Type, Scroll, Screenshot, and App management with reduced token usage compared to full-desktop alternatives.