"Control applications in macOS" matching MCP servers:

An MCP server that enables AI applications to access 20+ model providers (including OpenAI, Anthropic, Google) through a unified interface for text and image generation.

Enables AI assistants to see, control, and debug PySide6 desktop applications without modifying their source code, by capturing screenshots, inspecting widget trees, performing clicks and typing, reading logs, and running Python inside the app process.

An MCP Server that enables LLMs to build real-time 3D web applications in the PlayCanvas Editor.

Enhanced fork of Google's Colab MCP, pre-registers all 7 notebook tools at startup (get_cells, add/run/update/delete/move_cell, add_text_cell), adds programmatic GPU control (T4/L4/A100) via OAuth, and fixes the "Disconnected from local server" issue with IPv4-only bind, PNA CORS headers, and stale-tab dedup. Works on Chrome, Edge, Windows, macOS, Linux.

Enables controlling OriginLab Origin through MCP to read and write worksheets, build and style multi-panel graphs, and export figures, reporting what Origin actually did rather than what it was asked to do. Works from macOS or Linux against Origin running in a Windows VM.

An MCP server for managing, editing, and running Stata .do files, integrating with Claude Desktop to enable natural language control of Stata analysis on macOS.

Enables automatic generation of complete Maven projects (applications, plugins, libraries) with intelligent package detection, customizable file structure, and integrated ZIP export functionality.

Exposes vLLM capabilities to AI assistants, enabling chat completions, model management, and platform-aware container control with automatic detection of Docker/Podman and GPU availability across Linux, macOS, and Windows.

Enables AI assistants to build, test, run, and manage Apple platform projects (iOS, macOS, tvOS, watchOS, visionOS) directly through Xcode. Provides comprehensive control over Xcode projects, Swift packages, simulators, and development workflows without leaving your editor.

An MCP server that enables AI agents to debug .NET applications using netcoredbg. It supports core debugging tasks like setting breakpoints, stepping through code, and inspecting variables or stack traces.

A simple Model Context Protocol server implemented in TypeScript that enables communication with client applications (like Cursor) over standard input/output and includes a basic calculator tool as an example.

A server that integrates Flux's advanced image generation and manipulation features into AI coding assistants, enabling seamless text-to-image and image control workflows in IDEs like Cursor and Windsurf.

A FastMCP tool that enables control of Spotify through natural language commands in Cursor Composer, allowing users to manage playback, search for content, and interact with playlists.

A bridge between Figma designs and React implementations that enables pixel-perfect conversion of Figma designs into React applications by processing Figma file data into React-friendly format.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

A bridge that enables seamless integration of Ollama's local LLM capabilities into MCP-powered applications, allowing users to manage and run AI models locally with full API coverage.

A model context protocol server that enables applications to use stackzero-labs/ui components through the MCP protocol, supporting both standalone operation and integration with Claude Desktop and Cursor.

A Model Context Protocol (MCP) server for Adobe After Effects that enables AI assistants and other applications to control After Effects through a standardized protocol.

A server enabling integration between KoboldAI's text generation capabilities and MCP-compatible applications, with features like chat completion, Stable Diffusion, and OpenAI-compatible API endpoints.

A Python implementation of the Model Context Protocol (MCP) that connects client applications with AI models, primarily Anthropic's models, with setup instructions for local development and deployment.