React Native AI DevTools

Give your AI a way to verify its work on React Native.

Verification is what separates AI that guesses from AI that ships. For backend work, the agent runs the server and hits the endpoints. For web, it drives a browser. For desktop, it uses computer use. For React Native, the pieces are scattered across separate tools — this package brings them together.

One MCP server with logs, network capture, component inspection, taps, screenshots, OCR, and JS execution — all tightly integrated so your agent can move fluidly from "what happened?" to "what's on screen?" to "does the fix hold?" — chained into a single feedback loop your agent can drive end-to-end.

Get started

1. Setup rn-ai-devtools as an MCP server for your agent of choice
2. Setup UI automation helpers

Feedback & Feature Requests

Have an idea or found something that could be better? Head over to GitHub Discussions to share feedback, request features, and vote on what gets built next.

Features

Runtime Interaction

• Console Log Capture - Capture console.log, warn, error, info, debug with filtering and search. Note: on a cold start (first app launch), logs emitted before the MCP server connects are missed — subsequent reloads capture everything. Install the optional SDK to buffer logs from the very first line of app startup
• Network Request Tracking - Monitor HTTP requests/responses with headers, timing, and body content. Like logs, early network requests on cold start may be missed before the connection is established. Install the optional SDK for full capture from app startup including request/response bodies
• JavaScript Execution - Run code directly in your app (REPL-style) and inspect results
• Global State Debugging - Discover and inspect Apollo Client, Redux stores, Expo Router, and custom globals
• Bundle Error Detection - Get Metro bundler errors and compilation issues with file locations

Device Control

• iOS Simulator - Screenshots, app management, URL handling, boot/terminate (via simctl)
• Android Devices - Screenshots, app install/launch, package management (via ADB)
• Unified Tap - Single tap tool with automatic fallback chain: fiber tree → accessibility → OCR → coordinates. Auto-detects platform, accepts pixels from screenshots. Returns post-tap screenshot and verifies visual change by default
• UI Automation - Swipe, long press, text input, and key events on both platforms
• Accessibility Inspection - Query UI hierarchy to find elements by text, label, or resource ID
• OCR Text Extraction - Extract visible text with tap-ready coordinates via Google Cloud Vision (works on any screen content)

Multi-Device Debugging

• Connect All Devices - scan_metro automatically discovers and connects to all Bridgeless targets on each Metro port
• Device Targeting - Every tool accepts an optional device parameter for targeting specific devices by name (case-insensitive substring match)
• Per-Device Buffers - Logs and network requests are captured separately per device for clean debugging
• Cross-Platform Comparison - Debug iOS and Android side-by-side, comparing logs, network traffic, and component trees

Under the Hood

• Auto-Discovery - Scans Metro on ports 8081, 8082, 19000-19002 automatically
• Multi-Device Support - Connects to all Bridgeless targets simultaneously, with per-device log and network buffers
• Auto-Reconnection - Exponential backoff (up to 8 attempts) when connection drops
• Efficient Buffering - Circular buffers: 500 logs, 200 network requests
• Platform Support - Expo SDK 54+ (Bridgeless) and React Native 0.70+ (Hermes)

Setup

Claude Code Setup

No installation required - Claude Code uses npx to run the latest version automatically.

Global (all projects)

claude mcp add rn-ai-devtools --scope user -- npx react-native-ai-devtools

Project-specific

claude mcp add rn-ai-devtools --scope project -- npx react-native-ai-devtools

Manual Configuration

Add to ~/.claude.json (user scope) or .mcp.json (project scope):

{ "mcpServers": { "rn-ai-devtools": { "type": "stdio", "command": "npx", "args": ["react-native-ai-devtools"] } } }

Restart Claude Code after adding the configuration.

VS Code Copilot Setup

Requires VS Code 1.102+ with Copilot (docs).

Via Command Palette: Cmd+Shift+P → "MCP: Add Server"

Manual config - add to .vscode/mcp.json:

{ "servers": { "rn-ai-devtools": { "type": "stdio", "command": "npx", "args": ["-y", "react-native-ai-devtools"] } } }

Cursor Setup

Docs

Via Command Palette: Cmd+Shift+P → "View: Open MCP Settings"

Manual config - add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{ "mcpServers": { "rn-ai-devtools": { "command": "npx", "args": ["-y", "react-native-ai-devtools"] } } }

Android

Android works out of the box — all device control tools use ADB, which ships with Android Studio. Verify it's available:

adb devices

iOS Simulator — UI Automation Setup

iOS UI automation tools (tap, swipe, text input, accessibility queries) require a UI driver. Install one of the following:

Option A: AXe CLI (experimental)

AXe is a standalone CLI for iOS simulator automation. No daemon required — single binary, simple setup.

brew install cameroncooke/axe/axe

Verify: axe --version

Add env to your MCP server configuration:

{ "mcpServers": { "rn-ai-devtools": { "type": "stdio", "command": "npx", "args": ["react-native-ai-devtools"], "env": { "IOS_DRIVER": "axe" } } } }

Note: AXe text input only supports US keyboard layout characters.

Option B: IDB

IDB (iOS Development Bridge) is a tool built by Meta for automating iOS Simulators. Requires a background daemon.

brew install idb-companion

Verify: idb_companion --list 1

IDB is the default driver — no IOS_DRIVER env var needed.

What works without a UI driver:

Capability	Without IDB/AXe	With IDB/AXe
Screenshots	Yes (simctl)	Yes
App install/launch/terminate	Yes (simctl)	Yes
URL opening	Yes (simctl)	Yes
Boot simulator	Yes (simctl)	Yes
Tap / swipe / gestures	No	Yes
Text input	No	Yes
Accessibility tree queries	No	Yes
Element finding / waiting	No	Yes
Hardware buttons (Home, Lock)	No	Yes

Troubleshooting: If you see errors like "IDB is not installed" or "AXe is not installed" in tap results, install the appropriate driver with the commands above and retry.

Requirements

• Node.js 18+
• React Native app running with Metro bundler
• iOS UI automation: Facebook IDB (brew install idb-companion) or AXe CLI (brew install cameroncooke/axe/axe) — required for tap, swipe, text input, accessibility on iOS Simulator
• Optional for offline OCR fallback: Python 3.6+ (only needed when cloud OCR is unavailable, see OCR Setup)

Claude Code Skills

Pre-built skills for common debugging workflows — session setup, log inspection, network debugging, and more. See the skills guide for the full list and installation instructions.

Available Tools

See the full tool reference for all tools with descriptions. Key tools:

Tool	Description
scan_metro	Start here — scan for Metro servers and auto-connect
get_logs / search_logs	Capture and search console logs with filtering and summaries
get_network_requests	Monitor HTTP requests with method/status filtering
get_screen_layout	Screen map of visible components with positions, sizes, and text content
tap	Unified tap — auto-detects platform, tries fiber → accessibility → OCR → coordinates
execute_in_app	Run JS expressions in the app runtime (REPL-style)
ios_screenshot / android_screenshot	Take device screenshots

Usage

1. Start your React Native app:
   npm start

or

expo start 2. In Claude Code, scan for Metro:

Use scan_metro to find and connect to Metro  

3. Get logs:

Use get_logs to see recent console output  

Detailed Guides

Guide	Description
Console Logging	get_logs parameters, filtering, summary mode, TONL format, token optimization
Network Tracking	SDK setup for full capture, filtering, request details, statistics
App Inspection	Debug globals (Apollo, Redux, Expo Router), execute_in_app, limitations
Layout & Component Inspection	get_screen_layout, component tree, inspect_at_point, find_components
Device Interaction	Unified tap, platform-specific gestures, text input, key events
OCR Text Extraction	Cloud Vision OCR, offline fallback, language config, workflows
Claude Code Skills	Pre-built skills for session setup, debugging, and automation
Full Tool Reference	Complete list of all 40+ tools with descriptions

Supported React Native Versions

Version	Architecture	Engine	Status
Expo SDK 54+	Bridgeless (New Arch)	Hermes	✓ Fully supported
RN 0.76+	Bridgeless (New Arch)	Hermes	✓ Fully supported
RN 0.73 - 0.75	Bridge (Old Arch)	Hermes	✓ Fully supported (best network capture via CDP)
RN 0.70 - 0.72	Bridge (Old Arch)	Hermes / JSC	✓ Supported
RN < 0.70	Bridge	JSC	Not tested

How It Works

1. Fetches device list from Metro's /json endpoint
2. Connects to the main JS runtime via CDP (Chrome DevTools Protocol) WebSocket
3. Enables Runtime.enable to receive Runtime.consoleAPICalled events
4. Network capture via two paths:
   • With SDK: Reads from the SDK's in-app buffer via Runtime.evaluate — captures all requests from startup with full headers and bodies, including cold-start events that CDP would miss
   • Without SDK: Enables CDP Network.enable (on supported targets) or injects a JS fetch interceptor as fallback. On cold start, events emitted before the CDP connection is established are lost; subsequent reloads capture everything
5. Stores logs and network requests in circular buffers for retrieval

Connection Management

Explicit Connection

The server does not auto-connect on startup. Call scan_metro to discover and connect to Metro servers. This prevents multiple MCP server instances (from parallel agent sessions) from competing for the single CDP WebSocket slot, which would cause connection thrashing and dropped tools.

Graceful Shutdown

When the MCP server process is terminated (SIGINT/SIGTERM), it closes all CDP WebSocket connections and cancels reconnection timers, freeing the CDP slot immediately for other sessions.

Reconnection on Disconnect

When the connection to Metro is lost (e.g., app restart, Metro restart, or network issues):

1. The server automatically attempts to reconnect
2. Uses exponential backoff: 500ms, 1s, 2s, 4s, 8s (up to 8 attempts)
3. Re-fetches device list to handle new WebSocket URLs
4. Preserves existing log and network buffers

Connection Gap Warnings

If there was a recent disconnect, get_logs and get_network_requests will include a warning:

[WARNING] Connection was restored 5s ago. Some logs may have been missed during the 3s gap.

Monitor Connection Health

Use get_connection_status to see detailed connection information:

=== Connection Status ===

--- React Native (Port 8081) ---
  Status: CONNECTED
  Connected since: 2:45:30 PM
  Uptime: 5m 23s
  Recent gaps: 1
    - 2:43:15 PM (2s): Connection closed

Troubleshooting

No devices found

• Make sure the app is running on a simulator/device
• Check that Metro bundler is running (npm start)

Wrong device connected

The server prioritizes devices in this order:

1. React Native Bridgeless (SDK 54+)
2. Hermes React Native
3. Any React Native (excluding Reanimated/Experimental)

Logs not appearing

• Ensure the app is actively running (not just Metro)
• Try clear_logs then trigger some actions in the app
• Check get_apps to verify connection status
• On cold start (first launch): The CDP connection is established after the app's early initialization code has already run, so startup logs and network requests are missed. Once connected, use reload_app — the subsequent reload captures everything from the beginning because the connection is already in place. To capture startup events on every launch, install the optional SDK

Telemetry & Data Collection

This package collects anonymous usage telemetry to help improve the product. No personal information is collected.

What is collected

Data	Purpose
Tool names	Which MCP tools are used most
Success/failure	Error rates for reliability improvements
Duration (ms)	Performance monitoring
Session start/end	Retention analysis
Platform	macOS/Linux/Windows distribution
Server version	Adoption of new versions

Not collected: No file paths, code content, network data, or personally identifiable information.

Auto-registration

On first tool use, the package automatically registers your installation with our backend. No account or login is required — the Tool works fully out of the box.

Why we do this: The product roadmap includes features that build on installation identity — project memory (your AI assistant gets smarter with every session by remembering navigation maps, element signatures, and debug patterns), cloud sync across machines, team collaboration with shared debugging context, and a Pro dashboard for managing installations and subscriptions. Auto-registration lays the groundwork so these features work seamlessly when they ship, without requiring a disruptive setup step later.

What is sent:

• A random installation ID (UUID)
• A device fingerprint (one-way SHA-256 hash — cannot be reversed to recover its components)
• Platform, hostname, OS version, and server version

What is NOT sent: No source code, file paths, console logs, network data, component names, or any content from your app. The fingerprint exists solely to prevent installation hijacking — it ties your installation to your physical machine so no one else can claim it.

Registration is fire-and-forget — it never blocks your work, fails silently if the network is unavailable, and can be disabled entirely (see Opt-out below). See PRIVACY.md for full details on data handling, storage, and your rights.

Opt-out

To disable telemetry and auto-registration, add RN_DEBUGGER_TELEMETRY to the env field in your MCP server configuration:

{ "mcpServers": { "rn-ai-devtools": { "type": "stdio", "command": "npx", "args": ["react-native-ai-devtools"], "env": { "RN_DEBUGGER_TELEMETRY": "false" } } } }

All debugging tools work normally with telemetry disabled. For the complete privacy policy, see PRIVACY.md.

Tap failure artifacts

When the tap tool fails or produces no visible change on screen, the package uploads a small JSON bundle and up to three downscaled PNG screenshots (before, after, and after-with-marker showing exactly where the tap landed) to a 10-day-retention store so we can diagnose and fix tap reliability issues. We do not use this data to train AI models and do not share it with third parties. See PRIVACY.md for details.

To opt out while keeping the rest of the package working:

"env": { "RN_AI_DEVTOOLS_DISABLE_FAILURE_ARTIFACTS": "1" }

License

MIT