"Developing a Flutter application with embedded React Native" matching MCP servers:

Provides AI agents with accurate, version-aware documentation for React Native, Expo, React Navigation, and Ignite by automatically detecting project dependencies and fetching matching documentation.

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.

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

Provides comprehensive React Native development assistance with expert-level automated code remediation, security vulnerability fixes, performance optimization, and production-ready code generation. Includes testing suite generation, dependency management, and accessibility compliance tools.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

An MCP server for React Native development with Expo, offering automated code remediation, refactoring, testing, and analysis tools to accelerate development and enforce best practices.

Enables AI agents to compile, flash, erase, and read serial output from embedded development boards, with guardrails such as budget limits, serial port mutexes, and mandatory human confirmation for destructive operations.

Connects AI coding clients to a running Flutter app's Dart VM Service so they can stream live exceptions with stack traces, logs, network calls, frame timings, memory, rebuild attribution and navigation state as structured tool results. It also correlates that evidence into root-cause diagnoses with confidence and suggested fixes, and streams everything to a browser dashboard.

Provides Flutter and Dart reference data, code generation, live API lookups, and a verified sample corpus for AI coding assistants, enabling efficient Flutter development with accurate guidance and boilerplate generation.

An MCP server for source-grounded, page-cited evidence retrieval tailored for embedded and firmware development, returning verbatim snippets with exact citations or 'no match' to prevent fabrications.

Lets AI assistants read, command, and debug microcontrollers over a serial connection via MCP. Provides tools for serial port discovery, reading serial output, sending commands, and decoding register values.

Gives AI coding agents live, cached access to current Flutter, Dart SDK and pub.dev documentation returned as clean markdown, resolving class names, identifiers and packages on demand instead of relying on a model's memory. Also provides ranked name search over thousands of classes and a politeness layer with robots.txt compliance, throttling, conditional GETs and request budgets.

An MCP server that lets AI agents see, tap, type, scroll, and assert inside live Flutter apps — no pre-written tests required.

Enables building Flutter and Dart apps through a multi-agent system that orchestrates specialized agents for UI design, backend development, testing, and deployment.

Enables Android APK reverse engineering and Flutter runtime injection through a six-step pipeline of decompile, analyze, synthesize, inject, patch, and repackage. Provides MCP tools for authorized security research and penetration testing.

Enables debugging Flutter apps on Android by exposing the widget tree and source locations, supporting hot reload and pixel-level UI diffs, along with filtered Android logs, crash traces, and device interaction.

MCP server providing AI coding assistants with documentation and source code for @gaddario98 React packages, including tools for listing packages, retrieving docs and types, and searching source.

An MCP server that wraps Flutter CLI tools into structured, agent-friendly tools for AI coding agents, with features like two-phase test results, output capping, and managed app lifecycle.

A privacy-first MCP server for locally managing job, fellowship, and graduate-school applications. It offers tools for tracking application status, analyzing role fit, generating LaTeX CV/cover letters, interview prep, and discovering public jobs from ATS APIs.

基于MCP协议的嵌入式板卡远程管理工具，提供串口、SSH和本地PowerShell的交互能力，支持会话管理、一键登录等功能。

Enables AI agents to inspect, log, and control React Native apps on Android emulators or iOS simulators, including UI tree, tap, scroll, and hot reload.

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.

Exposes tools that let an agent read a CV, search the Arbeitnow job board for Berlin AI/ML working student roles, score each vacancy against the CV, draft cover letters whose every claim cites CV facts, and queue them for human approval. The same tools can be driven from other MCP clients such as Claude Desktop, with scoring done deterministically in code and limits enforced outside the prompt.

MCP server for Zotero 10+. Read and write your library entirely offline through Zotero's native local API. No plugin, no API key, no cloud.

Enables orchestrator agents to route coding tasks to native CLI worker agents via MCP, providing tools for agent discovery, task submission, waiting, inspection, and cancellation.

Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.

Enables AI agents to profile React applications, detect performance bottlenecks, and automatically apply fixes like memoization and code hoisting.

An MCP server that lets Claude Code delegate durable background tasks, reasoning profiles, thread resumption, and native image generation to your local Codex CLI.

Enables AI assistants to query accurate, up-to-date documentation for a React component library, including component lists, search, props, allowed values, defaults, and validated JSX usage examples over stdio.

An MCP server that runs parallel AI agents to analyze React components for performance issues, including unnecessary re-renders, memoization errors, bundle size problems, and profiling concerns.