"Linux Foundation" matching MCP servers:

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

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.

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

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

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

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

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.

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.

Controls a real Linux desktop from any MCP host. Reads accessibility trees, takes screenshots, and drives clicks, scrolls, and keystrokes across GNOME, KDE/KWin, Hyprland, i3, and COSMIC.

Enables AI agents to automate real desktop applications across Windows, Linux, and macOS using incremental screen perception, accessibility trees, OCR, and window management, dramatically reducing token usage compared to screenshot-per-step approaches.

Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.

Enables agents to inspect repositories, manage Golden Packs, plan golden flows, and run asynchronous validation tasks over MCP, providing a deterministic foundation for project-specific workflows.