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Build autonomous AI agents for React Native and Expo apps. Provides AI-native UI traversal, tool calling, and structured reasoning.

Package Exports

  • @mobileai/react-native
  • @mobileai/react-native/generate-map
  • @mobileai/react-native/package.json

Readme

Agentic AI for React Native

Add an autonomous AI agent to any React Native app — no rewrite needed. Wrap your app with <AIAgent> and get: natural language UI control, real-time voice conversations, and a built-in knowledge base. Fully customizable, production-grade security, performant, and lightweight. Plus: an MCP bridge that lets any AI connect to and test your app.

Two names, one package — pick whichever you prefer:

npm install @mobileai/react-native
# — or —
npm install react-native-agentic-ai

🤖 AI Agent — Autonomous UI Control

AI Agent autonomously controlling a React Native app UI via natural language

🧪 AI-Powered Testing — Test Your App in English, Not Code

AI-Powered Testing via Model Context Protocol — finding bugs in React Native app without test code

Google Antigravity running 5 checks on the emulator and finding 5 real bugs — zero test code, zero selectors, just English.


npm

npm

license

platform

Two names, one package — install either: @mobileai/react-native or react-native-agentic-ai

⭐ If this helped you, star this repo — it helps others find it!


🧠 How It Works — Structure-First Agentic AI

What if your AI could understand your app the way a real user does — not by looking at pixels, but by reading the actual UI structure?

That's what this SDK does. It reads your app's live UI natively — every button, label, input, and screen — in real time. The AI understands your app's structure, not a screenshot of it.

No OCR. No image pipelines. No selectors. No annotations. No view wrappers.

The result: an AI that truly understands your app — and can act on it autonomously.

This SDK Screenshot-based AI Build It Yourself
Setup <AIAgent> — one wrapper Vision model + custom pipeline Months of custom code
How it reads UI Native structure — real time Screenshot → OCR Custom integration
AI agent loop ✅ Built-in multi-step ❌ Build from scratch ❌ Build from scratch
Voice mode ✅ Real-time bidirectional
Custom business logic useAction hook Custom code Custom code
MCP bridge (any AI connects) ✅ One command
Knowledge base ✅ Built-in retrieval

✨ What's Inside

Ship to Production

🤖 Autonomous AI Agent — Natural Language UI Automation

Your users describe what they want in natural language. The SDK reads the live screen, plans a sequence of actions, and executes them end-to-end — tapping buttons, filling forms, navigating screens — all autonomously. Powered by Gemini. OpenAI is also supported as a text mode alternative.

  • Zero-config — wrap your app with <AIAgent>, done. No annotations, no selectors
  • Multi-step reasoning — navigates across screens to complete complex tasks
  • Custom actions — expose any business logic (checkout, API calls, mutations) via useAction
  • Knowledge base — AI queries your FAQs, policies, product data on demand
  • Human-in-the-loop — native Alert.alert confirmation before critical actions

🎤 Real-time Voice AI Agent — Bidirectional Audio with Gemini Live API

Full bidirectional voice AI powered by the Gemini Live API (Gemini only). Users speak naturally; the agent responds with voice AND controls your app simultaneously.

  • Sub-second latency — real-time audio via WebSockets, not turn-based
  • Full UI control — same tap, type, navigate, custom actions as text mode — all by voice
  • Screen-aware — auto-detects screen changes and updates its context instantly

💡 Speech-to-text in text mode: Install expo-speech-recognition and a mic button appears in the chat bar — letting users dictate messages instead of typing. This is separate from voice mode.


Supercharge Your Dev Workflow

🔌 MCP Bridge — Connect Any AI to Your App

Your app becomes MCP-compatible with one prop. Any AI that speaks the Model Context Protocol — editors, autonomous agents, CI/CD pipelines, custom scripts — can remotely read and control your app.

The MCP bridge uses the same AgentRuntime that powers the in-app AI agent. If the agent can do it via chat, an external AI can do it via MCP.

MCP-only mode — just want testing? No chat popup needed:

<AIAgent
  showChatBar={false}
  mcpServerUrl="ws://localhost:3101"
  apiKey="YOUR_KEY"
  navRef={navRef}
>
  <App />
</AIAgent>

🧪 AI-Powered Testing via MCP

The most powerful use case: test your app without writing test code. Connect your AI (Antigravity, Claude Desktop, or any MCP client) to the emulator and describe what to check — in English. No selectors to maintain, no flaky tests, self-healing by design.

Skip the test framework. Just ask:

Ad-hoc — ask your AI anything about the running app:

"Is the Laptop Stand price consistent between the home screen and the product detail page?"

YAML Test Plans — commit reusable checks to your repo:

# tests/smoke.yaml
checks:
  - id: price-sync
    check: "Read the Laptop Stand price on home, tap it, compare with detail page"
  - id: profile-email
    check: "Go to Profile tab. Is the email displayed under the user's name?"

Then tell your AI: "Read tests/smoke.yaml and run each check on the emulator"

Real Results — 5 bugs found autonomously:

# What was checked Bug found AI steps
1 Price consistency (list → detail) Laptop Stand: $45.99 vs $49.99 2
2 Profile completeness Email missing — only name shown 2
3 Settings navigation Help Center missing from Support section 2
4 Description vs specifications "breathable mesh" vs "Leather Upper" 3
5 Cross-screen price sync Yoga Mat: $39.99 vs $34.99 4

📦 Installation

Two names, one package — pick whichever you prefer:

npm install @mobileai/react-native
# — or —
npm install react-native-agentic-ai

No native modules required by default. Works with Expo managed workflow out of the box — no eject needed.

Optional Dependencies

📸 Screenshots — for image/video content understanding
npx expo install react-native-view-shot
🎙️ Speech-to-Text in Text Mode — dictate messages instead of typing
npx expo install expo-speech-recognition

Automatically detected. No extra config needed — a mic icon appears in the text chat bar, letting users speak their message instead of typing. This is separate from voice mode.

🎤 Voice Mode — real-time bidirectional voice agent
npm install react-native-audio-api

Expo Managed — add to app.json:

{
  "expo": {
    "android": { "permissions": ["RECORD_AUDIO", "MODIFY_AUDIO_SETTINGS"] },
    "ios": { "infoPlist": { "NSMicrophoneUsageDescription": "Required for voice chat with AI assistant" } }
  }
}

Then rebuild: npx expo prebuild && npx expo run:android (or run:ios)

Expo Bare / React Native CLI — add RECORD_AUDIO + MODIFY_AUDIO_SETTINGS to AndroidManifest.xml and NSMicrophoneUsageDescription to Info.plist, then rebuild.

Hardware echo cancellation (AEC) is automatically enabled — no extra setup.


🚀 Quick Start

Add one line to your metro.config.js — the AI gets a map of every screen in your app, auto-generated on each dev start:

// metro.config.js
require('@mobileai/react-native/generate-map').autoGenerate(__dirname);

Or generate it manually anytime:

npx @mobileai/react-native generate-map

Without this, the AI can only see the currently mounted screen — it has no idea what other screens exist or how to reach them. Example: "Write a review for the Laptop Stand" — the AI sees the Home screen but doesn't know a WriteReview screen exists 3 levels deep. With a map, it sees every screen in your app and knows exactly how to get there: Home → Products → Detail → Reviews → WriteReview.

2. Wrap Your App

React Navigation

import { AIAgent } from '@mobileai/react-native'; // or 'react-native-agentic-ai'
import { NavigationContainer, useNavigationContainerRef } from '@react-navigation/native';
import screenMap from './ai-screen-map.json'; // auto-generated by step 1

export default function App() {
  const navRef = useNavigationContainerRef();

  return (
    <AIAgent
      // ⚠️ Prototyping ONLY — don't ship API keys in production
      apiKey="YOUR_API_KEY"

      // ✅ Production: route through your secure backend proxy
      // proxyUrl="https://api.yourdomain.com/ai-proxy"
      // proxyHeaders={{ Authorization: `Bearer ${userToken}` }}

      navRef={navRef}
      screenMap={screenMap} // optional but recommended
    >
      <NavigationContainer ref={navRef}>
        {/* Your existing screens — zero changes needed */}
      </NavigationContainer>
    </AIAgent>
  );
}

Expo Router

In your root layout (app/_layout.tsx):

import { AIAgent } from '@mobileai/react-native'; // or 'react-native-agentic-ai'
import { Slot, useNavigationContainerRef } from 'expo-router';
import screenMap from './ai-screen-map.json'; // auto-generated by step 1

export default function RootLayout() {
  const navRef = useNavigationContainerRef();

  return (
    <AIAgent
      apiKey={process.env.AI_API_KEY!}
      navRef={navRef}
      screenMap={screenMap}
    >
      <Slot />
    </AIAgent>
  );
}

Choose Your Provider

The examples above use Gemini (default). To use OpenAI for text mode, add the provider prop. Voice mode is not supported with OpenAI.

<AIAgent
  provider="openai"
  apiKey="YOUR_OPENAI_API_KEY"
  // model="gpt-4.1-mini"  ← default, or use any OpenAI model
  navRef={navRef}
>
  {/* Same app, different brain */}
</AIAgent>

A floating chat bar appears automatically. Ask the AI to navigate, tap buttons, fill forms, answer questions.

Knowledge-Only Mode — AI Assistant Without UI Automation

Set enableUIControl={false} for a lightweight FAQ / support assistant. Single LLM call, ~70% fewer tokens:

<AIAgent enableUIControl={false} knowledgeBase={KNOWLEDGE} />
Full Agent (default) Knowledge-Only
UI analysis ✅ Full structure read ❌ Skipped
Tokens per request ~500-2000 ~200
Agent loop Up to 25 steps Single call
Tools available 7 2 (done, query_knowledge)

🗺️ Screen Mapping — Navigation Intelligence

By default, the AI navigates by reading what's on screen and tapping visible elements. Screen mapping gives the AI a complete map of every screen and how they connect — via static analysis of your source code (AST). No API key needed, runs in ~2 seconds.

Setup (one line)

Add to your metro.config.js — the screen map auto-generates every time Metro starts:

// metro.config.js
require('@mobileai/react-native/generate-map').autoGenerate(__dirname);

// ... rest of your Metro config

Then pass the generated map to <AIAgent>:

import screenMap from './ai-screen-map.json';

<AIAgent screenMap={screenMap} navRef={navRef}>
  <App />
</AIAgent>

That's it. Works with both Expo Router and React Navigation — auto-detected.

What It Gives the AI

Without Screen Map With Screen Map
AI sees only the current screen AI knows every screen in your app
Must explore to find features Plans the full navigation path upfront
Deep screens may be unreachable Knows each screen's navigatesTo links
No knowledge of dynamic routes Understands item/[id], category/[id] patterns

Disable Without Removing

<AIAgent screenMap={screenMap} useScreenMap={false} />
Advanced: Watch mode, CLI options, and npm scripts

Manual generation:

npx @mobileai/react-native generate-map

Watch mode — auto-regenerates on file changes:

npx @mobileai/react-native generate-map --watch

npm scripts — auto-run before start/build:

{
  "scripts": {
    "generate-map": "npx @mobileai/react-native generate-map",
    "prestart": "npm run generate-map",
    "prebuild": "npm run generate-map"
  }
}
Flag Description
--watch, -w Watch for file changes and auto-regenerate
--dir=./path Custom project directory

💡 The generated ai-screen-map.json is committed to your repo — no runtime cost.


🧠 Knowledge Base

Give the AI domain knowledge it can query on demand — policies, FAQs, product details. Uses a query_knowledge tool to fetch only relevant entries (no token waste).

Static Array

import type { KnowledgeEntry } from '@mobileai/react-native'; // or 'react-native-agentic-ai'

const KNOWLEDGE: KnowledgeEntry[] = [
  {
    id: 'shipping',
    title: 'Shipping Policy',
    content: 'Free shipping on orders over $75. Standard: 5-7 days. Express: 2-3 days.',
    tags: ['shipping', 'delivery'],
  },
  {
    id: 'returns',
    title: 'Return Policy',
    content: '30-day returns on all items. Refunds in 5-7 business days.',
    tags: ['return', 'refund'],
    screens: ['product/[id]', 'order-history'], // only surface on these screens
  },
];

<AIAgent knowledgeBase={KNOWLEDGE} />
<AIAgent
  knowledgeBase={{
    retrieve: async (query: string, screenName?: string) => {
      const results = await fetch(`/api/knowledge?q=${query}&screen=${screenName}`);
      return results.json();
    },
  }}
/>

🔌 MCP Bridge Setup — Connect AI Editors to Your App

Architecture

┌──────────────────┐                  ┌──────────────────┐    WebSocket     ┌──────────────────┐
│  Antigravity     │  Streamable HTTP │                  │                 │                  │
│  Claude Desktop  │ ◄──────────────► │ @mobileai/       │ ◄─────────────► │  Your React      │
│  or any MCP      │    (port 3100)   │  mcp-server      │   (port 3101)   │  Native App      │
│  compatible AI   │  + Legacy SSE    │                  │                 │                  │
└──────────────────┘                  └──────────────────┘                 └──────────────────┘

Setup in 3 Steps

1. Start the MCP bridge — no install needed:

npx @mobileai/mcp-server

2. Connect your React Native app:

<AIAgent
  apiKey="YOUR_API_KEY"
  mcpServerUrl="ws://localhost:3101"
/>

3. Connect your AI:

Google Antigravity

Add to ~/.gemini/antigravity/mcp_config.json:

{
  "mcpServers": {
    "mobile-app": {
      "command": "npx",
      "args": ["@mobileai/mcp-server"]
    }
  }
}

Click Refresh in MCP Store. You'll see mobile-app with 2 tools: execute_task and get_app_status.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "mobile-app": {
      "url": "http://localhost:3100/mcp/sse"
    }
  }
}
Other MCP Clients
  • Streamable HTTP: http://localhost:3100/mcp
  • Legacy SSE: http://localhost:3100/mcp/sse

MCP Tools

Tool Description
execute_task(command) Send a natural language command to the app
get_app_status() Check if the React Native app is connected

Environment Variables

Variable Default Description
MCP_PORT 3100 HTTP port for MCP clients
WS_PORT 3101 WebSocket port for the React Native app

🔌 API Reference

<AIAgent> Props

Prop Type Default Description
apiKey string API key for your provider (prototyping only).
provider 'gemini' | 'openai' 'gemini' LLM provider for text mode.
proxyUrl string Backend proxy URL (production).
proxyHeaders Record<string, string> Auth headers for proxy.
voiceProxyUrl string Dedicated proxy for Voice Mode WebSockets.
voiceProxyHeaders Record<string, string> Auth headers for voice proxy.
model string Provider default Model name (e.g. gemini-2.5-flash, gpt-4.1-mini).
navRef NavigationContainerRef Navigation ref for auto-navigation.
maxSteps number 25 Max agent steps per task.
maxTokenBudget number Max total tokens before auto-stopping the agent loop.
maxCostUSD number Max estimated cost (USD) before auto-stopping.
showChatBar boolean true Show the floating chat bar.
enableVoice boolean true Enable voice mode tab.
enableUIControl boolean true When false, AI becomes knowledge-only.
screenMap ScreenMap Pre-generated screen map from generate-map CLI.
useScreenMap boolean true Set false to disable screen map without removing the prop.
instructions { system?, getScreenInstructions? } Custom system prompt + per-screen instructions.
customTools Record<string, ToolDefinition | null> Override or remove built-in tools.
knowledgeBase KnowledgeEntry[] | KnowledgeRetriever Domain knowledge the AI can query.
knowledgeMaxTokens number 2000 Max tokens for knowledge results.
mcpServerUrl string WebSocket URL for MCP bridge.
accentColor string Accent color for the chat bar.
theme ChatBarTheme Full chat bar color customization.
onResult (result) => void Called when agent finishes.
onBeforeStep (stepCount) => void Called before each step.
onAfterStep (history) => void Called after each step.
onTokenUsage (usage) => void Token usage per step.
onAskUser (question) => Promise<string> Handle ask_user inline — agent waits for your response.
stepDelay number Delay between steps (ms).
router { push, replace, back } Expo Router instance.
pathname string Current pathname (Expo Router).
debug boolean false Enable SDK debug logging.

🎨 Customization

// Quick — one color:
<AIAgent accentColor="#6C5CE7" />

// Full theme:
<AIAgent
  accentColor="#6C5CE7"
  theme={{
    backgroundColor: 'rgba(44, 30, 104, 0.95)',
    inputBackgroundColor: 'rgba(255, 255, 255, 0.12)',
    textColor: '#ffffff',
    successColor: 'rgba(40, 167, 69, 0.3)',
    errorColor: 'rgba(220, 53, 69, 0.3)',
  }}
/>

useAction — Custom AI-Callable Business Logic

import { useAction } from '@mobileai/react-native'; // or 'react-native-agentic-ai'

function CartScreen() {
  const { cart, clearCart, getTotal } = useCart();

  useAction('checkout', 'Place the order and checkout', {}, async () => {
    if (cart.length === 0) return { success: false, message: 'Cart is empty' };

    // Human-in-the-loop: AI pauses until user taps Confirm
    return new Promise((resolve) => {
      Alert.alert('Confirm Order', `Place order for $${getTotal()}?`, [
        { text: 'Cancel', onPress: () => resolve({ success: false, message: 'User denied.' }) },
        { text: 'Confirm', onPress: () => { clearCart(); resolve({ success: true, message: `Order placed!` }); } },
      ]);
    });
  });
}

useAI — Headless / Custom Chat UI

import { useAI } from '@mobileai/react-native'; // or 'react-native-agentic-ai'

function CustomChat() {
  const { send, isLoading, status, messages } = useAI();

  return (
    <View style={{ flex: 1 }}>
      <FlatList data={messages} renderItem={({ item }) => <Text>{item.content}</Text>} />
      {isLoading && <Text>{status}</Text>}
      <TextInput onSubmitEditing={(e) => send(e.nativeEvent.text)} placeholder="Ask the AI..." />
    </View>
  );
}

Chat history persists across navigation. Override settings per-screen:

const { send } = useAI({
  enableUIControl: false,
  onResult: (result) => router.push('/(tabs)/chat'),
});

🔒 Security & Production

Backend Proxy — Keep API Keys Secure

<AIAgent
  proxyUrl="https://myapp.vercel.app/api/gemini"
  proxyHeaders={{ Authorization: `Bearer ${userToken}` }}
  voiceProxyUrl="https://voice-server.render.com"  // only if text proxy is serverless
  navRef={navRef}
>

voiceProxyUrl falls back to proxyUrl if not set. Only needed when your text API is on a serverless platform that can't hold WebSocket connections.

Next.js Text Proxy Example
import { NextResponse } from 'next/server';

export async function POST(req: Request) {
  const body = await req.json();
  const response = await fetch('https://generativelanguage.googleapis.com/...', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json', 'x-goog-api-key': process.env.GEMINI_API_KEY! },
    body: JSON.stringify(body),
  });
  return NextResponse.json(await response.json());
}
Express WebSocket Proxy (Voice Mode)
const express = require('express');
const { createProxyMiddleware } = require('http-proxy-middleware');

const app = express();
const geminiProxy = createProxyMiddleware({
  target: 'https://generativelanguage.googleapis.com',
  changeOrigin: true,
  ws: true,
  pathRewrite: (path) => `${path}${path.includes('?') ? '&' : '?'}key=${process.env.GEMINI_API_KEY}`,
});

app.use('/v1beta/models', geminiProxy);
const server = app.listen(3000);
server.on('upgrade', geminiProxy.upgrade);

Element Gating — Hide Elements from AI

<Pressable aiIgnore={true}><Text>Admin Panel</Text></Pressable>

Content Masking — Sanitize Before LLM Sees It

<AIAgent transformScreenContent={(c) => c.replace(/\b\d{13,16}\b/g, '****-****-****-****')} />

Screen-Specific Instructions

<AIAgent instructions={{
  system: 'You are a food delivery assistant.',
  getScreenInstructions: (screen) => screen === 'Cart' ? 'Confirm total before checkout.' : undefined,
}} />

Lifecycle Hooks

Hook When
onBeforeStep Before each agent step
onAfterStep After each step (with full history)
onBeforeTask Before task execution
onAfterTask After task completes

🛠️ Built-in Tools

Tool What it does
tap(index) Tap any interactive element — buttons, switches, checkboxes, custom components
long_press(index) Long-press an element to trigger context menus
type(index, text) Type into a text input
scroll(direction, amount?) Scroll content — auto-detects edge, rejects PagerView
slider(index, value) Drag a slider to a specific value
picker(index, value) Select a value from a dropdown/picker
date_picker(index, date) Set a date on a date picker
navigate(screen) Navigate to any screen
wait(seconds) Wait for loading states before acting
capture_screenshot(reason) Capture the screen as an image (requires react-native-view-shot)
done(text) Finish the task with a response
ask_user(question) Ask the user for clarification
query_knowledge(question) Search the knowledge base

📋 Requirements

  • React Native 0.72+
  • Expo SDK 49+ (or bare React Native)
  • Gemini API key — Get one free, or
  • OpenAI API key — Get one

Gemini is the default provider and powers all modes (text + voice). OpenAI is available as a text mode alternative via provider="openai". Voice mode uses gemini-2.5-flash-native-audio-preview (Gemini only).

📄 License

MIT © Mohamed Salah

👋 Let's connect — LinkedIn