"Information about cursors (general use or specific context)" matching MCP servers:

An MCP server that lets an AI agent use a real terminal the way a person does: type, press keys, click, read the screen, take a screenshot.

Enables agents to interact with CLI applications like vim, htop, and gdb by sending key inputs and capturing terminal output through tmux sessions.

MCP server that enables Claude to control your computer, similar to Anthropic's computer use but easy to set up locally.

Enables MCP agents to automate real GUI applications on headless desktops, providing background mouse/keyboard control, window/process management, screenshots, and safe human handoff without disturbing the user's desktop.

A low-level computer-use MCP server that exposes raw desktop control (mouse, keyboard, shell, windows, processes, screenshots, etc.) to MCP clients like Claude Code and Codex.

Local + remote terminal interaction control MCP Server. Lets AI agents control interactive TUI programs the way a human would.

Pixel-level browser automation MCP server that drives a real Chrome browser using screenshots as vision input and OS-level mouse/keyboard as output, evading anti-bot detection.

Enables MCP clients to observe and control the Windows desktop through the UI Automation accessibility tree — no vision model required — by exposing tools for reading windows and interactive elements, clicking, typing, scrolling, shortcuts, PowerShell, screenshots, virtual desktops, web scraping, file operations and persistent memory, including background-window control without stealing focus. An optional agent mode adds a single natural-language task tool that runs the full upstream agent loop when an LLM provider is configured.

Enables Claude to fully control a Windows desktop with native screen capture, low-level input injection, game-grade input, and play-testing capabilities.

A production-grade macOS MCP server exposing 33 tools for full desktop automation, including mouse, keyboard, screenshot, clipboard, and window control.

Provides 146 MCP tools for AI agents to control macOS, including screenshots, mouse, keyboard, window management, app automation, file system, OCR, and built-in app semantics like Calendar, Mail, Safari, Music, Messages. Enables full control over macOS through natural language.

Enables AI agents to see and operate a Windows PC through mouse, keyboard, screenshots, OCR, window control, and shell commands.

Enterprise-grade macOS MCP server that gives AI agents eyes, hands, and a terminal, enabling screen capture, mouse/keyboard control, shell commands, and file operations.

Retired. This MCP wrapper is no longer maintained. Check is now a Claude Code hook: npx @golproductions/check@latest --install. 120 free messages a day. Details: golproductions.com/check

Enables AI assistants to create isolated Kubernetes Pod sessions for real-time shell command execution, file management, and Node.js code execution, with automatic TTL-based cleanup.

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

Connects AI assistants to a Kali Linux terminal for executing security tools, managing interactive shell sessions, and performing penetration testing, CTF challenges, and security research tasks.

An MCP server for integrating AI models with client applications, allowing for structured interactions with APIs using command-line arguments for authentication and configuration.

A comprehensive production-ready MCP server with AI integration, plugin management, and web-based administration. Features multi-database support, RAG capabilities, SSH/SFTP access, and a built-in plugin hub for managing the MCP ecosystem.

A minimal MCP server for UW Hyak (klone) that exposes tools to run shell commands and write files remotely, along with documentation resources for klone-specific utilities.

Enables AI agents to securely use real secrets (API keys, database passwords) by requiring human approval for each release, ensuring secrets never enter the model's context.

Enables AI to execute registered system commands across platforms using a stable program + args interface, without requiring shell-specific syntax or tool discovery.

An MCP server that intelligently filters and compresses tool outputs to reduce context window usage, saving up to 90% of tokens by removing noise such as passing tests and redundant information.

Enables LLM agents to run commands, manage interactive or background sessions, and transfer files on remote hosts under policy-based authorization, command classification, approval gates, and full audit logging. Supports per-host profiles with role-based rules, streaming file transfers that keep bytes out of model context, and a configurable approval policy for destructive or privileged work.

Runs as an MCP server providing file system operations, shell execution, and system information tools, allowing Claude or any MCP client to edit files and control the machine.

Enables secure remote command execution and file operations over SSH/SFTP with automatic authentication resolution. Features built-in diagnostics that identify connection issues—such as stale host keys, unloaded agents, or permission errors—and provide specific commands to fix them.

Provides AI coding agents with structured, evidence-based diagnostics about the local development environment, detecting tech stack, runtime mismatches, dependency state, services, ports, and Git status without exposing secrets or using network calls.

Enables AI agents to ask users for credentials, secrets, and sensitive data through local browser forms that the model never sees, then resolve and use those values only at approved points of use. Also supports blind web capture, SSH key provisioning, and writes to .env files, SQL databases, and APIs, with the agent receiving only structural results.

Problem: MCP clients can't efficiently use Xcode CLI tools because the build and simulator listing commands return more than 50k tokens, exceeding MCP limits. Solution: MCP tooling using progressive disclosure with intelligent caching.

A secure Model Context Protocol server that allows AI models to safely interact with Windows command-line functionality, enabling controlled execution of system commands, project creation, and system information retrieval.