"How to Find and Fix Bugs in a React Native App" matching MCP servers:

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.

An MCP server that connects to your React Native application debugger

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

Enables AI agents such as Cursor and Claude Desktop to read a running debugger's captured console logs and network sessions, inspect full request/response payloads, diagnose crashes and failed API calls, and trigger React Native reloads or the developer menu.

Provides AI agents with visibility into React applications by exposing tools to inspect component state, props, and performance metrics. It enables debugging and state analysis for both web and React Native applications through the Model Context Protocol.

Streams live React profiler data to AI agents, enabling them to analyze performance and suggest specific, actionable fixes for slow components.

Enables AI assistants to inspect React Native app performance including memory, rendering, frames, and network requests, providing plain-language summaries and shareable reports.

Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

Provides read-only access to App Store Connect analytics, sales, finance, and customer review data, with tools to fetch and parse reports from Apple's Analytics Reports API and other report endpoints.

Enables terminal and MCP clients to manage Google Play, App Store Connect, and AdMob through official APIs, including listings, releases, reviews, vitals, sales, and reports, with dry-run safety by default.

Enables tracing every tool call from a ChatGPT app into LangSmith, one run per tool call, grouped per conversation thread. Provides thread-level evaluation and monitoring of tool interactions.

Enables management of App Store Connect resources including app reviews, TestFlight crashes, analytics reports, and Xcode Cloud workflows through natural language or AI agents.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Brings interactive blue-team security operations into AI hosts, enabling alert triage, attack discovery, case management, detection rules, threat hunting, and sample data generation with rich inline UIs.

Enables analysis and management of iOS/macOS apps via the App Store Connect API, including app management, reviews, sales reports, analytics, performance metrics, and TestFlight.

Self-hosted Nightingale (n9e) includes a native Streamable HTTP MCP server at /mcp for querying alerts, rules, metrics, logs, hosts and dashboards with the caller's existing permissions. Users deploy the Nightingale server themselves; the implementation and deployment documentation are in the main repository, and the official website is https://n9e.io.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

Enables MCP clients to retrieve lab performance scores and field Core Web Vitals data for web pages via Google APIs.

Enables AI assistants to access App Store Connect data including financial metrics, subscription analytics, app performance data, and revenue insights. Provides real-time iOS app metrics through secure API integration with rate limiting and comprehensive reporting capabilities.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Checks MCP servers by URL, npm package, or official MCP Registry search, reporting availability, response speed, exposed tools, resources, and prompts. It flags changes since prior runs as breaking, warning, or info using saved snapshots.

Monitoring that agents set up for themselves — cron jobs, CI/CD pipelines and AI agent runs.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Enables AI assistants to interact with inSCADA systems via the Model Context Protocol, providing 39 tools for live data, alarms, scripts, historical analysis, charts, and more.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

An MCP server that gives AI agents hands-on control of a live React Native app, enabling UI taps, screenshots, UI/component trees, native logs, and JS/React profiling to debug, verify fixes, and diagnose performance issues.

MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.

Enables an AI assistant such as Claude to read and edit the self-hosted network inventory: search and manage entries, check live TCP reachability, map hosts, link and derive relationships, inspect topology, compare configured read-only sources like Docker, OPNsense, AdGuard and Traefik against what is declared, surface conflicts and new devices, and review the audit log.

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.