"Evaluating an Expo Go App and Associated React Native Code in an Android Emulator" matching MCP servers:

An MCP server for React Native development with Expo, offering automated code remediation, refactoring, testing, and analysis tools to accelerate development and enforce best practices.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

Publishes a spending-summary tool alongside an interactive HTML view, letting people click a category in the answer to fetch the individual expense records behind that total. Keeps calculations and their supporting evidence together in a single inspectable flow.

MCP server for Android emulator automation via ADB.

Enables AI agents to control the Android Emulator through adb, including booting AVDs, installing and managing apps, interacting with the UI, taking screenshots, reading logs, and more.

Provides AI agents with accurate, version-aware documentation for React Native, Expo, React Navigation, and Ignite by automatically detecting project dependencies and fetching matching documentation.

Connects AI agents to a running React Native app so they can see the screen, tap and type, and inspect logs, network traffic, and state without any SDK or code changes. Composite tools let an agent run a whole interaction flow in a single call instead of one round trip per tap.

MCP server that gives AI coding agents hands, eyes and a mechanic's ear for React Native development.

Provides comprehensive tools for React Native development, automating project initialization, version management, upgrades, Expo integration, and development workflows through AI assistance.

Creates new Expo React Native apps from a Feature-Sliced Design template and configures store deployment settings.

Provides comprehensive React Native development assistance with expert-level automated code remediation, security vulnerability fixes, performance optimization, and production-ready code generation. Includes testing suite generation, dependency management, and accessibility compliance tools.

An MCP server that connects to your React Native application debugger

Enables automation and monitoring of React Native apps by providing tools to tap, swipe, screenshot, inspect component state, profile renders, and mock network requests via MCP.

Bridges React Native DevTools, enabling AI assistants to debug, profile, and inspect React Native applications through a standardized protocol.

Exposes mobile system capabilities as MCP tools so AI agents can access clipboard, location, calendar, contacts, files, storage, networking, and device connectivity through standard transports. It applies permission policies and native adapters for integration into mobile apps without bundling an AI agent or host bridge.

Enables an agent to inspect and interact with Android emulators or physical devices via ADB, capturing UI snapshots, tapping nodes, typing text, and reading app logs.

Enables automated testing and development of Expo/React Native apps through session-based Expo dev server management and Maestro UI automation tools for tapping, text input, screenshots, and flow execution.

Provides AI assistants offline fuzzy search, precise section retrieval, and section listing over bundled mobile-development documentation, enabling natural-language lookups of components, hooks, guides, and best practices.

Enables AI assistants to execute Expo and EAS operations including project setup, cloud builds, OTA updates, app submission, and diagnostics.

Enables an AI agent to drive an Android app under development on a local emulator or connected device through adb, observing the screen and performing taps, swipes, text entry, key presses, waits, screenshots, logcat and crash inspection. It is restricted to debug builds installed via Run in Android Studio, so agents can exercise only the app being developed.

Enables AI assistants and automation agents to interact with Cisco CUCM Emulator instances through dynamically generated tools for telephony operations, call simulation, routing policies, CDR buffers, and optional offline mock state.

Enables AI agents to interact with the app via MCP tools and resources, supporting self-improvement through goal-setting and metrics tracking on Cloudflare Workers.

A single MCP server that orchestrates Expo CLI, Metro, and adb for local Expo project management, including device interaction and session summaries.

Enables agents to launch and control interactive terminal sessions, inspecting screen text and formatting while sending keyboard and mouse input. Supports real pseudoterminals with resizing, snapshots, and session lifecycle management.

Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.

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 an AI client to control an Android emulator or USB device over ADB by selecting a device, inspecting the UI hierarchy, and performing taps, swipes, text entry, key presses, and app launches. It relies only on Android platform-tools and exposes a compatible tool surface for phone automation.

An MCP server that gives AI agents full control of Android devices and emulators through plain ADB — no companion APK, no extra daemon, no telemetry.

An MCP server that runs parallel AI agents to analyze React components for performance issues, including unnecessary re-renders, memoization errors, bundle size problems, and profiling concerns.

Indexes any TypeScript / React / Next.js repo into a queryable code graph and exposes 13 MCP tools — who-renders, who-calls, find-references, blast-radius, find-cycles, dead-code orphans, and local semantic search — so agents query structure instead of reading whole files. Built on ts-morph, so edges are resolved, not grepped.