"How to execute custom code in a Linux Docker container" matching MCP servers:

A secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.

Enables Codex to inspect, run commands in, and apply patches to whitelisted Docker containers.

Enables LLMs to execute shell commands and perform file operations on a Linux system, exposing tools like execute_command, read_file, write_file, and more.

A secure Docker-based environment that allows AI assistants to safely execute code without direct access to the host system by running all code within isolated containers.

More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.

Give Claude Desktop full desktop control on Linux/X11: screenshot, mouse, keyboard, windows, clipboard, app launch. Zero-dependency MCP extension, MIT-licensed.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

Enables read-only Linux system diagnostics and troubleshooting on local and remote RHEL-based systems via SSH, including services, processes, logs, network, and storage analysis.

An MCP server for read-only Linux system administration and diagnostics on RHEL-based systems via SSH. It enables users to troubleshoot remote hosts by accessing system information, services, logs, and network configurations through natural language.

A powerful Python-based Model Context Protocol (MCP) server that enables AI assistants to manage remote Linux machines over SSH directly from your chat interface.

Enables managing Docker containers and Docker Compose projects on Synology NAS via SSH, with auto-privilege escalation and full compatibility with Synology Container Manager.

Enables AI agents to remotely control Linux machines via SSH with 35 tools for session management, file transfer, system administration, Docker, and CTF operations.

Provides AI assistants with the ability to control Linux desktop environments through tools for file management, application launching, and system operations like clipboard access. It includes a multi-level security model to manage permissions for safe, elevated, and restricted actions.

Enables spawning ephemeral Linux sandbox containers using Docker and executing commands through an interactive TTY interface. Supports collaborative terminal sessions where both AI clients and humans can simultaneously interact with the same container.

Enables remote execution of Linux commands via SSH, supporting system monitoring, file operations, and secure authentication with configurable safety controls.

MCP server that enables AI assistants to manage SSH terminal sessions, execute commands, and automate server operations through natural language, with multi-tab support and session persistence.

Enables full Linux desktop control including windows, mouse, keyboard, clipboard, audio, screenshots, OCR, accessibility, and system management through MCP-compatible AI agents.

Exposes a Linux host with shell, Python, and filesystem tools as MCP tools over HTTPS, enabling AI agents to execute commands and manage files remotely.

Remote Linux operations via SSH, exposed as an MCP server, with tools for filesystem, systemd, Docker, network, and more, using per-user AD authentication and optional sudo elevation.

An MCP server for managing Ubuntu/Linux systems, enabling AI assistants to execute commands, manage services, files, logs, and packages via local or SSH connection.