"Linux Foundation" matching MCP servers:

Enables AI agents to drive a Linux/X11 desktop via AT-SPI accessibility-tree perception and element-level actions, avoiding screenshots and coordinate clicking.

Provides safe Linux desktop automation for Codex through focused MCP tools for inspecting, clicking, typing, dragging, and verifying native applications on Wayland and X11.

A standalone MCP server for Linux desktop control, enabling screenshots, mouse/keyboard input, app/window management, and clipboard access via a Python bridge.

Enables background window capture and input automation without moving the cursor or stealing focus, working across Windows, Linux X11, and Wayland systems.

An MCP server that gives AI agents local Linux desktop control through tools for screenshots, accessibility, mouse, keyboard, and reliable text input.

Enables Claude Code and Codex to see and drive an X11 desktop through screenshots, mouse, keyboard, and accessibility-tree actions while keeping the user's own pointer and focus separate.

Enables AI agents to remotely control computers via VNC, including mouse movement, clicking, keyboard input, text entry, and screen capture across Windows, Linux, and macOS systems.

MCP server enabling AI agents to control a real Linux browser with live view, human takeover, and safety guardrails.

A foundation for building interactive applications using the Model Context Protocol that integrates AI capabilities with Magic UI components.

MCP server that inspects older repos, identifies stale guidance, and installs a managed foundation for better Copilot work including instructions, objectives, specialist agents, and insights.

A basic TypeScript implementation of the Model Context Protocol (MCP) server designed as a starting point for MCP development. Provides a minimal foundation for building custom MCP servers with stdio configuration for local integration with VS Code and GitHub Copilot.

A foundation for creating custom Model Context Protocol servers that can integrate with AI systems, providing a simple BMI calculator tool as an example implementation.

An MCP server that enables automated dataset creation and custom object detection model training through natural language interactions. It integrates foundation models like GroundedSAM for auto-labeling and supports training specialized YOLOv8 models using local or Unsplash images.

Gives an AI agent its own fleet of disposable Linux microVMs on hardware you control, with tools to spawn, execute commands in, fork from identical disk states, list, and destroy them. Enables safe parallel exploration and cleanup all within an isolated VM boundary.

Linux desktop HAL for AI agents. One daemon, one socket, every desktop action. GNOME, KDE, Hyprland, X11. Ships in one command.

Exposes eight mmap_* tools that let an agent declare a system's ghost dependency design first, then light each node up as it is built and verified, with downward-only edges and evidence-backed green status. Clients get a live ledger of what exists, what is in progress right now, and which foundation has cracked.

Enables AI agents to see and control an existing Linux X11 desktop over SSH by taking screenshots and performing mouse, scroll, typing, and keyboard-shortcut actions across browsers, terminals, file managers, and other apps.

Enables AI agents to perform autonomous penetration testing on any Linux distribution via SSH with persistent tmux sessions, supporting interactive tools like Metasploit, reverse shells, and complex multi-step security workflows.

Enables tool-capable AI models to operate a private Linux desktop and headless browser, with terminal, file, and application controls, while keeping your physical mouse and keyboard separate.

Enables strict resource governance for AI agent processes using Linux cgroup v2, enforcing CPU bandwidth, memory limits, and process limits to prevent resource overconsumption, runaway loops, and fork bombs.

Enables coding agents to control other application windows by providing primitives for clicking, typing, capturing screenshots, and window management. Supports macOS, Windows, and Linux.

Enables AI supervisors to delegate coding tasks to sandboxed coding-agent workers on a Linux machine, with isolated git worktrees, daemon-run tests, and structured results.

MCP server providing AI-friendly computer-use primitives (capture, detect, click) to let LLM agents drive desktop GUI applications on Windows, macOS, and Linux.

An LLM-native decision tracking system that captures unexpected engineering outcomes as 'pressure events' to build a persistent learning foundation. It enables AI assistants to manage cases, log surprises, and promote recurring insights into global or project-specific knowledge bases.

Enables AI agents to record desktop workflows from human demonstrations, save them as validated semantic skills, and replay them in an isolated Linux sandbox with deterministic verification and evidence-driven self-healing.

Enables AI agents to operate a complete Linux desktop through MCP, including applications, system windows, file managers, terminals, and browsers via AT-SPI element trees. It also provides noVNC access for humans to observe and take over the same desktop session.

Enables AI agents to play the Linux Steam game through exact engine state and rules, with engine-native movement, undo, menu, and level actions—no screenshots or OCR.

Grants Claude Code desktop-control capabilities on Linux, including screenshots, mouse movement and clicks, keyboard input, window listing and focusing, and clipboard access.

Provides an AI agent with a fixed, isolated Linux desktop workspace, enabling bounded screen capture, input control, and application launching via MCP.

Enables AI agents to automate Linux desktop GUI by launching and interacting with Wayland applications in isolated virtual KWin sessions, or connecting to live desktops for collaborative automation.