"Model-Controller-Presenter (MCP) for Building iOS Apps" matching MCP servers:

A Model Context Protocol (MCP) server for iOS Simulator automation. Enables AI assistants to visually interact with iOS apps running in the simulator.

Enables interaction with iOS simulators by providing tools to inspect UI elements, control UI interactions, and manage simulators through natural language commands.

Enables retrieval of compact APG pattern cards, such as button, modal, and dialog, through an MCP tool so clients can consult accessibility guidance.

An MCP server that provides comprehensive tools for managing iOS simulators, including device control, app lifecycle management, and UI automation. It enables developers to boot devices, install apps, capture screenshots, and simulate user interactions through natural language commands.

MCP server that drives the iOS Simulator via accessibility-tree snapshots with stable element refs, enabling LLMs to interactively find, tap, type, and inspect UI elements at sub-200ms latency.

Enables AI agents to manage iOS Simulator state declaratively through MCP tools for inventory, snapshot, diff, planning, and safe apply operations.

Enables iOS build, launch, and UI test automation on both simulators and physical devices through a single MCP server, with lease-based device ownership that prevents simulator and helper process leaks.

Enables driving an iOS Simulator from a model: taking screenshots, reading the UI tree, tapping, swiping, typing, managing app lifecycle and device state such as appearance, permissions, location, and notifications, without code signing or a physical device.

Enables AI assistants to diagnose and fix iOS app issues that cause App Store rejections, such as missing privacy manifests, permission strings, and test credentials, before submission.

An MCP server that lets an AI agent drive the iOS Simulator in a loop, enabling tapping, typing, swiping, reading the screen via the accessibility tree, and verifying app state.

MCP server for capturing iOS device screenshots using Appium, compatible with AI clients like Trae.

Exposes native iPhone device services and UI automation through MCP, enabling agents to inspect and control trusted iPhones via a unified interface.

Enables comprehensive control of iOS simulators and real devices through AI assistants, supporting app management, UI automation, screenshots, media operations, and location simulation for iOS development and testing workflows.

Enables AI agents to control iOS Simulators for UI/UX debugging, app management, and accessibility auditing via simctl, IDB, and ClaudeDebugKit.

Enables inspecting ONNX models, probing the deployment environment, and benchmarking inference latency and FPS either locally or on remote SSH targets such as Linux workstations and Jetson devices. Benchmark results are validated against FPS, P95 latency and model-size constraints to produce PASS/FAIL deployment gates.

Enables macOS users to inspect and automate iPhone Safari and Chrome WebKit sessions, including device and page discovery, runtime evaluation, console and network capture, DOM snapshotting, and page-level automation.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

A Model Context Protocol server that enables AI assistants to interact with iOS simulators, perform accessibility testing, manage apps, and automate complex iOS workflows.

Comprehensive MCP server for iOS Simulator automation, enabling AI agents to control simulators via tap, swipe, type, accessibility inspection, app debugging, and device management.

51-tool Model Context Protocol (MCP) server for Android ADB: inspect databases, capture screenshots, manage apps, edit SharedPreferences, and drive devices with AI agents.