"Apple TV" matching MCP servers:

Build, deploy, and debug Smart TV web apps on Samsung Tizen and LG webOS TVs from any AI agent.

Enables coding agents to verify work on live cloud devices by uploading builds, starting sessions, driving UI through UI-tree refs, reading logs, and taking screenshots on iOS, Android, Apple TV, and Android TV.

MCP server for semi-manual QA test execution on real Smart TVs (Tizen/webOS) and local Chrome via Chrome DevTools Protocol, enabling remote control, state inspection, and profiling.

Translation QA for i18n locale files. Deterministic validators — missing keys, placeholder drift, collapsed plurals, glossary breaches — that need no API key, plus a review tool that hands translation pairs and judging criteria back to the calling agent, so meaning-level review runs on the model your client already has. Translation with your own LLM key is optional. JSON, Flutter .arb, Apple .

Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.

A local, stdio-only Model Context Protocol server that lets coding agents inspect, control, and test Apple iOS Simulators and Google Android Emulators. It exposes 29 typed tools for device lifecycle, app management, UI automation, screenshots, logs, permissions, location, and platform-specific test conditions.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

MCP server for controlling Android, Fire TV, and Android TV devices through ADB, enabling device management, app operations, screenshots, UI dumps, and OBS recording.

Enables AI assistants to manage Apple App Store Connect resources like apps, builds, TestFlight, and reviews through natural language.

Enables AI clients to drive a UI-testing toolbox with 35 tools, including a headless Playwright runner, live Chromium browser with screenshots, test management, and read-only database queries, all through the Model Context Protocol.

Discovery router for the agent-device CLI with status, install, help, prompts, and resources.

Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.

Enables AI agents to operate and view the Vega Virtual Device through MCP: press remote keys, take screenshots, record video with sound, wait for screen changes, and check the TV safe area.

Connects AI coding clients like OpenCode, Codex, and Claude Code to Xcode and Apple development tools, enabling builds, tests, simulator and device management, profiling, asset handling, and more through natural language.

Enables AI assistants to programmatically create, execute, and analyze Apache JMeter performance tests. It supports automated bottleneck detection, report generation, and distributed testing management through natural language.

Apple App Store Pre-Flight Guideline Auditor & Privacy Manifest Generator

Provides a read-only MCP bridge that lets Claude Web inspect workspace files, git state, and recorded test results while Codex remains the sole executor of changes.

Provides LLMs and AI agents safe, structured, read-only access to verification artifacts for deterministic triage and root-cause analysis. Supports UVM, cocotb, and SystemVerilog verification ecosystems.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.