"Information about the software application Trello" matching MCP servers:

Enables LLMs to list, open, and close installed software on Windows, macOS, and Linux through natural language.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Provides tools to monitor host system health including CPU load, disk usage, and network status while enabling file system management tasks like searching and moving files. It includes built-in safety guards to prevent operations on critical system directories.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables AI agents to automate local software management workflows including installation, uninstallation, updates, and environment recommendations. It provides a standardized, non-interactive interface for managing system applications and tracking software versions safely.

MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.

macOS automation for AI assistants: 17 typed tools for window management, application menus, keyboard input, clipboard, browser tabs, screenshots, displays and Apple Shortcuts, driven through AppleScript and JXA. Menu clicks are self-correcting — a wrong item returns the actual menu contents so the model can retry with the right one.

Provides native macOS computer control tools including mouse and keyboard simulation, screenshot capture, and application management for MCP-compatible agents. It enables AI assistants to directly interact with the macOS operating system and installed apps through standard tool calls.

A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.

A virtual Linux desktop as an MCP server, shipped in Docker. Agents drive screen, mouse, keyboard across any GUI — browsers, IDEs, office suites, Wine/Windows apps, legacy software — many in parallel.

Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.

Enables full control of macOS by executing AppleScript commands through an MCP server, allowing automation of tasks, application control, and system management.

Enables AI to remotely control macOS systems via VNC with full desktop capabilities including screenshots, mouse control, keyboard input, and application management. Includes a web-based chat interface for natural language control.

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Exposes Windows system information and control tools including hardware stats, network details, and process monitoring. It enables AI applications to retrieve real-time data about CPU, memory, drives, and active system processes.

Enables AI assistants to automate macOS through AppleScript and JXA by providing 44 tools for application management, window control, and UI interaction. It allows for comprehensive system control including screen capture, keyboard and mouse simulation, and system information retrieval.

A simple MCP server that provides accurate date and time information to Claude models, ensuring they always use the correct current date and time when creating time-sensitive content.

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 remote control and automation of Android devices through the Model Context Protocol, supporting UI interactions, app management, ADB commands, screenshots, and device information retrieval via AutoBot API.