"Learning about MCP for iOS and macOS development" matching MCP servers:

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

Connects LLMs to your macOS Shortcuts library, enabling interactive workflows, discovery, and management through AppleScript and CLI integration.

MCP server for the Oura Ring API v2, enabling natural language queries about sleep, readiness, activity, heart rate, and more.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Provides AI coding assistants with access to AccelByte Gaming Services (AGS) Extend SDK functions and models through searchable symbols and detailed documentation. Helps generate SDK code by exposing context about available functions, models, and templates for creating Extend app projects across multiple languages (Go, C#, Java, Python).

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Provides access to PatternFly React documentation, development rules, and component schemas through MCP tools, enabling AI assistants to help developers build applications with PatternFly components following best practices.

Enables AI assistants to print documents, manage print queues, and control printers on macOS/Linux systems via the CUPS printing system. Supports printing PDFs, text files, and other formats with options like duplex printing, landscape orientation, and multiple copies.

Enables AI assistants to automate mobile app testing and development for iOS and Android through natural language interactions. Supports intelligent element identification, session management, automated test generation, and comprehensive device interactions including clicks, swipes, screenshots, and app management.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

Enables Codex to interact with the user's local OmniFocus database on macOS, allowing task management, project creation, and tag operations through natural language.

Enables ChatGPT Web to securely control a trusted local computer through an OpenAI Secure MCP Tunnel, letting it perform file, process, Git, and other system operations on Windows, macOS, and Linux.

A local bridge that lets MCP clients inspect, export, and modify Figma files through a development Figma plugin.

Enables users to manage API keys and perform Aptos Build actions through MCP-compatible interfaces like Claude and Cursor. This server facilitates development workflows on the Aptos blockchain by integrating directly with the Aptos Build platform.

Integrates front-end development servers with AI tools, enabling browser automation, console log capture, screenshot management, and HMR event monitoring.

Habitica MCP server built with Effect v4, currently exposing a hello-world tool, resource, and prompt over stdio for early development and testing.