"Resources for Learning Linux" matching MCP servers:

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

MCP server for managing Proxmox VE resources, VM/CT lifecycle, snapshots, backups, and clones via natural language.

MCP server to give every agent an ephemeral Linux sandboxes for executing shell commands.

A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.

A private MCP server that lets ChatGPT create, manage, and operate Box by ASCII Linux environments through secure MCP tools.

Provides a local, isolated Linux VM sandbox for AI agents using Apple's Virtualization.framework, enabling fast command execution (~60ms) and package management without cloud costs.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

Enables AI assistants to run Kali Linux security tools in an isolated Docker container for tasks like network scanning, port checking, and service enumeration.

Private MCP server exposing the ascii Box API as shell and file tools, letting agents like ChatGPT or Claude drive Linux boxes.

An MCP server that allows AI agents to remotely control Windows, Linux, and macOS systems via VNC. It provides tools for mouse and keyboard interaction, text input, and screen capturing.

A Model Context Protocol server for conducting Linux binary analysis and guest system forensics within QEMU virtual machines. It enables automated VM lifecycle management, memory dumping, and interactive debugging workflows for analyzing processes and artifacts.

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

Linux sandboxes for AI agents, each a Firecracker microVM. Run code, keep files, pause and wake with memory kept, snapshot and fork.

A remote MCP bridge that lets MCP clients use Modal sandboxes for Linux execution, dependency installation, Git operations, GPU jobs, and invoking deployed Modal Functions.

Enables AI agents to operate disposable Linux computers via MCP, providing tools for shell, file read/write, directory listing, and port exposure. It also supports browser automation and integration with any MCP-compatible client.

Enables managing RunPod compute for the Learning-to-Swim replication through natural language, including pod lifecycle, SSH/rsync file transfer, detached training jobs, and supervised runs with cost guardrails.

Enables interaction with Proxmox VE for managing VMs, containers, storage, and cluster resources via natural language through the Model Context Protocol.

MCP server for Apple container to manage, build, inspect, and diagnose Linux containers on macOS directly from AI agents.

Enables AI models to securely query and manage virtual machines and virtualized resources via the libvirt API through the Model Context Protocol.

A server tool for running Deep Learning models that offers Shell execution, Ngrok connectivity, and Docker container hosting with support for multiple AI frameworks including Anthropic, Gemini, and OpenAI.