"How to control macOS settings or functions" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

An MCP Server that provides a natural language interface to Google Cloud Resource Settings API, enabling users to view and manage settings for Google Cloud resources through conversation.

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 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.

An MCP server that enables AI assistants to send native macOS notifications with automatic project detection and categorization. It includes logging capabilities for all notifications to provide an audit trail of system alerts.

Enables Claude to inspect and drive native macOS app UIs during development via an in-process view tree and screenshot renderer, without requiring screen recording permission.

An MCP server that enables AI assistants like Claude to send native macOS notifications with tmux integration, allowing notifications to focus specific tmux sessions when clicked.

MCP server to control Arc Browser on macOS via AppleScript, enabling tab, window, space, and page operations along with frontend/backend development tools like network monitoring, console capture, and API testing.

Portable governance control-promotion CLI and MCP server.

A Model Context Protocol server that enables direct integration with macOS Calendar application using AppleScript, allowing users to create, list, and search calendar events without requiring OAuth setup.

Local-first macOS MCP server for searching files, running approved Shortcuts, managing Homebrew packages, and working with local models, with read-only defaults and optional gated mutations.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and fetching weather data to demonstrate basic tool implementation and API integration patterns.

Enables one coding agent to inspect, configure, debug, and repair another agent over stdio MCP, with redacted reads and confirm-gated writes and restarts.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Enables safe, structured control of Blender on Windows via a standalone STDIO MCP server, providing seven tools to inspect scenes, list and edit materials, transform objects, add modifiers, set smooth shading, and export assets without arbitrary code execution.

Routes one brief to the right image model across 60+ (gpt-image-1.5, Ideogram 3, Recraft V4, Flux), validates the output, and fans out to iOS/Android/PWA/favicon/visionOS/Flutter bundles. Works without an API key via Pollinations, HF Inference, Stable Horde, or host-LLM inline SVG.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

The control plane for AI prompts that scores, enforces policy, locks config, and audits every prompt decision.