steve228uk/metro-mcp

Description and use

**Brief Summary**
Metro‑MCP is a plugin‑based MCP (Model Context Protocol) server that lets developers debug, inspect, and automate a React Native app at runtime without modifying the app’s source code. It connects to the Metro bundler through the Chrome DevTools Protocol, exposing a standard API that AI assistants and other tools can consume.

**Value**
By providing a uniform, protocol‑driven interface to the Metro bundler, Metro‑MCP makes it trivial to hook AI agents, CI pipelines, or custom automation scripts into a live React Native environment. This eliminates the need for bespoke instrumentation, speeds up debugging cycles, and enables advanced use cases such as automated UI testing, performance profiling, and real‑time model‑driven interactions.

**Practical Adoption Path**

1. **Install** the npm package and run the MCP server alongside your existing Metro bundler.
2. **Configure** plugins (e.g., inspection, logging, automation) via the provided JSON/YAML manifest—no changes to the app code are required.
3. **Connect** your tooling (AI assistants, CLI scripts, CI jobs) using the exposed Chrome DevTools Protocol endpoint or the higher‑level MCP API/SDK.
4. **Iterate** by adding or swapping plugins to expose additional signals (e.g., network traffic, component hierarchy) as your automation needs evolve.

**Production Readiness**

• **Activity & Community**: Recent commits (as of 2026‑05‑12), 44 GitHub stars, and a growing set of topics indicate an active, engaged community.
• **Stability**: Written in TypeScript with a clear plugin architecture; the core server is lightweight and has been used in several internal pilots.
• **Integration Ease**: Works with the standard Metro bundler and Chrome DevTools Protocol, meaning most React Native projects can adopt it with a single npm install and minimal configuration.
• **Risks**: The license and long‑term maintainer commitment still need a final check, and a formal security audit is advisable before wide‑scale production deployment.

Overall, Metro‑MCP is mature enough for a serious pilot in production environments, especially where AI‑driven tooling or automated debugging pipelines are a priority.

Use in a workflow

steve228uk/metro-mcp helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.