"Creating an MCP (Master Control Program) with any API" matching MCP servers:

Turn any CLI tool into an MCP server by leveraging its --help output, enabling natural language interaction with tools like gh, az, git, etc.

Enables execution of arbitrary CLI tools and shell scripts by defining them in YAML configuration files as MCP Tools. Supports custom shells (bash, Python, Node.js, Deno), input parameters passed as environment variables, and flexible timeout settings.

A local MCP server that controls two Codex CLI agent instances via tmux, enabling parallel agent operations with lifecycle management, status classification, and secure path handling.

Enables controlling an Android device from an MCP client via ADB, including wireless debugging discovery, UI-tree inspection, and performing taps, swipes, typing, app actions, and shell commands without relying on screen coordinates.

Provides full control of a macOS system, enabling AI agents to execute shell commands, run AppleScript, manage files and processes, and perform human-like GUI interactions such as clicking, dragging, scrolling, and typing, with a screenshot-based perception loop.

Manage local/SSH/WinRM remote hosts via MCP, providing tools for exec, filesystem, screen, process, serial console, and configuration.

MCP server that enables AI to fully control macOS — mouse, keyboard, terminal, screenshots, window management, UI element detection, and provides AI-optimized information reporting.

Enables comprehensive Linux desktop agent capabilities for Ubuntu/Debian systems, including system state monitoring, package management, persistent terminal sessions, and desktop control via mouse, keyboard, and screen capture, with support for multiple remote machines and a built-in permission system.

Enables comprehensive Android device control over ADB, including UI automation, screen capture/recording, app management, file operations, and log/notification access, with a built-in permission system.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

Enables AI services like Claude and Cursor to remotely control a Mac by executing shell commands, managing files, and running AppleScript for UI automation. Access is secured through OAuth 2.0 authentication and encrypted tunnels to protect remote interactions.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

Enables local/remote execution infrastructure through the official Codex Runtime, providing shell, files, Git, sessions, browser, computer use, recoverable tasks, multi-host routing, dynamic MCP integration, and skill lifecycle management.

A safety-first MCP server enabling file inspection/editing, allowlisted command execution, process listing, and optional desktop automation. It emphasizes security with disabled writes/commands/GUI by default and local feature gates.

A production-grade MCP server that lets AI cloud services control and manage your Linux server securely via HTTP/SSE.

Controls a Linux host through structured interfaces like systemd, journald, and D-Bus for service management, journal queries, power operations, and more, with safety guards to prevent accidental damage.

Enables comprehensive control over macOS GUI elements including mouse, keyboard, window management, and screen capture. It allows for automated system interactions and script execution while maintaining safety by blocking potentially destructive deletion commands.

A minimal MCP server that exposes a run_command tool over stdio, enabling command execution within a Docker container.

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