react-native-dev-mcp

react-native-dev-mcp

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

Category
访问服务器

README

react-native-dev-mcp

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

CI npm node license

Coding agents are good at writing React Native code and bad at everything around it: putting the app on a device, seeing what it logs, and understanding why the native build exploded into 4,000 lines of Gradle. This server closes that loop with three pillars:

Pillar What the agent gets
🤲 Device control One uniform interface over simctl + adb: list/boot devices, install/launch apps, deep links, screenshots, demo status bar. The agent never needs to know which platform it's driving.
👀 Runtime bridge Connects to Metro's inspector (CDP/Hermes, RN 0.76+ "Fusebox"). Streams console.* and uncaught errors into a cursor-based buffer, and runs evaluate_js inside the live app — inspect Redux/Zustand state, trigger navigation, verify the fix actually worked. Zero app code changes.
🔧 Build diagnostics Runs xcodebuild/Gradle as background jobs and parses the log against a community-maintained signature database of known RN failures, returning {errorType, file, line, probableCause, suggestedFix} instead of a log dump. Also parses any existing log offline.

Works with Expo and bare React Native CLI, RN 0.76+ (tested on 0.80+). The server is environment-aware: on Windows/Linux, iOS tools are never even registered, and every failure returns a structured remediation the agent can act on. Start with the doctor tool.

Install

Requires Node 22+. The server runs on your machine over stdio.

Claude Code

claude mcp add rn-dev -- npx -y react-native-dev-mcp

Or per-project, in .mcp.json:

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

Codex CLI

In ~/.codex/config.toml:

[mcp_servers.rn-dev]
command = "npx"
args = ["-y", "react-native-dev-mcp"]

Cursor / Claude Desktop / others

Any MCP client that speaks stdio works — point it at npx -y react-native-dev-mcp. Useful flags: --project-root <path>, --metro-port <port>, --eager-metro, --verbose.

Try asking your agent

Once installed, talk to your agent in plain language — it picks the right tools:

"Run my app on Android and figure out why it's broken at startup."

"Boot an iPhone simulator, build and install the app, then screenshot the login screen."

"The iOS build is failing. Diagnose it, apply the suggested fix and rebuild until it's green."

"Watch the console while I tap through checkout and summarize any errors you see."

"What's in the Redux store right now? Read the auth slice from the running app."

"Open the deep link myapp://profile/42 and verify it lands on the right screen."

The loop

A typical agent session against a real app:

doctor                       → toolchains ok, Metro running, project: expo · RN 0.85
list_devices                 → iPhone 16 Pro (booted)
run_build {platform: "ios"}  → job a1b2c3d4
get_build_status {jobId}     → ❌ failed · "Sandbox not in sync with Podfile.lock"
                               → fix: run pod install (tool run_pod_install)
run_pod_install              → ✅
run_build → get_build_status → ✅ artifact: .../MyApp.app
install_app + launch_app     → app running
read_console {level:"error"} → "TypeError: cannot read property 'id' of undefined"
evaluate_js {expression:
  "globalThis.store.getState().auth"} → { user: null, … }   ← found it
(agent edits code) → reload_app → read_console → clean ✅
take_screenshot              → 📸 verified visually

Tools (20)

Environment · doctor Devices · list_devices boot_device shutdown_device install_app uninstall_app launch_app terminate_app open_url take_screenshot set_status_bar_demo Runtime · list_runtime_targets read_console evaluate_js reload_app Build · run_build get_build_status cancel_build run_pod_install parse_build_log

Full reference with schemas and error codes: documentation site.

Good to know

  • One debugger at a time (Hermes limitation). If React Native DevTools is attached, runtime tools return DEBUGGER_OCCUPIED with instructions. Close the DevTools tab and retry.
  • Builds never block. run_build returns a job id in <2s; poll with get_build_status (it long-polls up to 60s per call). Logs persist on disk and can be re-parsed any time with parse_build_log.
  • Token-frugal by design. Lists are collapsed and capped, console reads are cursor-based and deduped, build results carry at most 10 diagnostics plus a logPath escape hatch.

Contributing

The easiest high-impact contribution is a build error signature — pure YAML plus a log snippet, no TypeScript. See CONTRIBUTING.md. Development is spec-driven: every tool's contract lives in specs/.

License

MIT © Luiz Esper

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选