"A Dockerized Python Code Execution Environment" matching MCP servers:

Provides a sandboxed Docker environment for executing Python code against API endpoints, exposing tools for discovery, inspection, execution, and reuse.

Enables AI agents to execute terminal commands and Python code on the host system with session management and smart output handling, leveraging Agent Zero's proven implementation.

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

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables a single Antigravity IDE to explicitly drive multiple isolated Antigravity CLI workers, choosing each worker's account, model, skills, task, and expected outputs while the bridge executes those decisions over STDIO with SQLite-backed task state. It returns bounded logs, cancellable task control, and immutable artifact exports whose chunks and whole files can be verified by SHA-256.

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.

A comprehensive MCP implementation designed for fullstack development that enables code manipulation, terminal command execution, and system notifications. It provides an intelligent agent interface powered by Gemini to automate Python and Next.js development workflows.

Enables AI assistants to securely interact with IBM i (AS/400) systems via ODBC, supporting SQL queries, CL commands, source code reading, compilation, and spoolfile analysis.

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

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 minimal, containerized MCP server that exposes a Streamable HTTP transport with API key authentication, allowing secure access to MCP endpoints.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables AI assistants to execute code in isolated sandboxes with support for Python, JavaScript, and TypeScript, featuring intelligent caching and semantic search for code reuse.

Enables AI agents to interact programmatically with Claude Code CLI, managing sessions, streaming outputs, and handling permission requests.

Creates short-lived, offline JavaScript sandbox containers for safe code execution via MCP, with no network access and strict resource limits.

Enables file reading with pagination and regex-based code search across a codebase using grep.

Delegates coding tasks to the local Claude Code CLI via MCP, offering run, review, and status tools for MCP-compatible agents.

Enables ISLI agents and MCP clients to dispatch natural-language coding and terminal tasks to a locally-installed Claude Code CLI, supporting both one-shot execution and persistent sessions with workspace and security controls.

Enables Claude to execute Minecraft commands and get tab completions through the MasterControl API. Allows remote command execution and command discovery while the player is online on a server.

Provides a secure interface to run Anthropic's Claude Code CLI as an MCP server, enabling task execution, persistent memory, and integration with MCP-enabled IDEs.