"Information about MongoDB, a database system" matching MCP servers:

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 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 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.

Enables system automation and control including command execution, process management, network tools, environment variables, disk usage, and service status.

A simple Model Context Protocol server that provides system information and public IP lookup tools for Claude Code.

A comprehensive Model Context Protocol server that enables AI assistants to interact with and manage Windows systems, providing capabilities for file system operations, process management, system information retrieval, registry operations, service management, network diagnostics, and performance monitoring.

Enables real-time monitoring of system resources including CPU, GPU (NVIDIA, Apple Silicon, AMD/Intel), memory, disk, network, and processes across Windows, macOS, and Linux platforms through natural language queries.

Provides Claude with real-time system monitoring capabilities, including CPU, memory, disk, network, battery, and internet speed metrics.

Enables LLMs to monitor system health, manage processes, execute shell commands, and inspect environment variables and directories.

Enables comprehensive system monitoring and diagnostics through 18 tools that provide detailed information about CPU, memory, disk usage, network interfaces, running processes, battery status, hardware details, and temperature monitoring. Allows users to query system information and performance metrics through natural language interactions.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables AI agents to monitor system resources and control media, brightness, volume, and other Windows PC functions through natural language commands.

Provides real-time Linux system monitoring for CPU load, memory usage, disk space, and process activity. This server enables users to retrieve comprehensive performance metrics and resource utilization data through a standardized interface.

A server that bridges the Model Context Protocol (MCP) to native OS functionalities, allowing AI assistants to open URLs, manage clipboard content, and retrieve date information.

Provides system monitoring and management capabilities for Claude CLI, allowing users to view system information, track resource usage, and manage processes through natural language commands.

Enables AI agents to interact with the Linux desktop through desktop notifications, interactive dialogs, shell command execution, and privileged command execution.

A lightweight MCP server that provides real-time hardware statistics including CPU, memory, disk, and NVIDIA GPU usage. It enables users to monitor system performance and retrieve comprehensive host machine specifications through a standardized interface.

A comprehensive MCP server that gives AI assistants full control over your desktop — monitor system resources, manage windows, capture screenshots, control the clipboard, launch applications, and more.

Enables interaction with the local file system and retrieval of system information. Provides tools for listing directories, reading files, getting current time, and basic greeting functionality.

Lets MCP clients discover and run AppleScript or JavaScript for Automation (JXA) to control macOS applications, inspect the system, or reuse scripts from a bundled knowledge base.

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

Enables MCP-speaking clients to control a real desktop via the computer_use tool, including clicking, typing, scrolling, dragging, key combos, app focus, and screen/accessibility capture. It also provides a verdict system that verifies whether input actions had their intended effect, with configurable approval modes.

A Model Context Protocol server that enables execution of AppleScript and JavaScript for Automation scripts on macOS, allowing programmatic control of applications and system functions through a rich knowledge base of pre-defined scripts.

Provides a Model Context Protocol server for executing AppleScript and JavaScript for Automation scripts on macOS, featuring a knowledge base of pre-defined scripts and supporting automation of macOS applications and system functions.

Provides AI agents with environmental sensing capabilities including current time, IP-based geolocation, system information, and hardware details. Enables more contextual and accurate AI responses based on user's environment.

Provides tools for reading and writing system clipboard data across Linux, macOS, Windows, and WSL platforms.

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.

Enables natural-language diagnosis of Linux system issues by providing sandboxed, typed tools for system, service, filesystem, and git inspection, with human approval for mutating actions.

Enables AI agents to query Windows process, window, and console information via structured JSON instead of screenshots, reducing token usage by 94-98%.

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.