"Improving React Native Development Experience" 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.

MCP servers for real-time development monitoring and interactive pair programming.

Captures and provides access to React Native console logs from Metro bundler, enabling AI assistants to retrieve, filter, and search app logs in real-time without manual copy/paste.

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 website QA auditing, covering SEO, performance, security, accessibility, and agent experience with 260+ rules and AI-optimized output for coding agents.

This MCP server enables real-time debugging and inspection of running React Native apps, providing access to console logs, errors, network requests, navigation state, storage, and performance profiling.

Allows AI assistants to query Tingyun (Wukong) platform monitoring data for App, Browser, and MiniProgram, covering performance, exceptions, user experience, network, and more via RUM REST API.

Enables users to ask about render performance in React and React Native apps via natural language, exposing tools for listing render hotspots and explaining component re-renders.

Provides structured MCP tools for local runtime observability and debugging of React Native/Expo apps on Android, enabling evidence-first diagnostics such as screenshots, UI trees, per-request network capture, performance metrics, and CDP-based console/heap/profiling exports.

Bridges your IDE to a running React Native/Expo mobile app over local Wi-Fi, providing live device status, app logs, and a combined standup snapshot.

An AI-powered server that analyzes system log files to identify errors/warnings and recommend fixes using FastMCP, LangGraph ReAct agents, and Anthropic Claude.

Enables agents to inspect React Native and Expo apps through React's runtime tree, identify source locations, act on elements without coordinates, and verify outcomes with assertions and runtime evidence.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.

Demonstrates agent-native platform onboarding with human-in-the-loop API key provisioning, plus live usage and rate-limit queries via Anthropic Admin APIs.

MCP-native agent evaluation and observability server. Log traces, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost thresholds), and track agent costs. Real-time dashboard, OTel-compatible spans. Self-hosted, MIT licensed.

Native Model Context Protocol (MCP) server turning AI coding agents into .NET runtime diagnosticians, memory forensic analysts, and CIL binary architects.

An MCP server that captures and analyzes function-level profiling data from NetEase Minecraft Bedrock Edition mods via the native Tracy profiler, enabling AI to identify performance hotspots and verify optimizations.

An MCP server that exposes macOS-native device trust signals — the facts about a Mac that cannot be gathered from a Linux container or a cloud runner. All tools are strictly read-only.

Enables MCP-compatible AI assistants to inspect projects, processes, ports, logs, HTTP endpoints, Git state, and development databases for local runtime diagnostics.

MCP-native LLM observability. Query your Spanlens traces, stats, cost anomalies, and savings from Cursor, Claude Desktop, or any MCP client. Open source (MIT).

Enables AI assistants to manage remote servers via SSH with 14 commands for execution, file transfer, auditing, and monitoring.

An MCP server for Action1, a cloud-native RMM platform, enabling remote monitoring, patch management, and endpoint management through Action1's API.

AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.