"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.

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

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

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 AI agents to run persistent Node.js REPL sessions that preserve state across evaluations, supporting top-level await, module loading, and per-session npm package installation.

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

Provides a persistent JavaScript kernel that treats any configured MCP server as a capability catalog, exposing all its tools to the model through just two tools (js and js_reset) while keeping the model-visible schema small and injecting host parameters like projectPath.

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 personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

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.

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

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

Enables secure Windows development automation by providing MCP tools for filesystem access, project builds, restricted PowerShell commands, and approved network fetches.

A secure JavaScript REPL server that enables executing code snippets in a sandboxed environment with memory protection, timeout handling, and comprehensive error reporting.

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

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.