"A framework for building cross-platform mobile applications using Flutter" matching MCP servers:

A framework for building MCP servers with built-in enterprise capabilities such as authentication, authorization, telemetry, audit logging, and data classification, allowing domain developers to focus on business logic while maintaining governance and compliance.

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.

A real-time server that provides Flutter/Dart documentation and pub.dev package information to AI assistants, ensuring they generate accurate and up-to-date Flutter code.

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

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 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.

MCP server orchestrating API-first cross-review between Claude, ChatGPT Codex, Gemini, DeepSeek, Grok, and Perplexity with unanimous convergence gates.

Enables AI coding assistants to search, retrieve, and reuse validated Flutter animations with documented pitfalls, directly integrable into Claude Code or Cursor.

A TypeScript framework for building Model Context Protocol (MCP) servers with automatic discovery and loading of tools, resources, and prompts.

Provides Flutter best practices, code analysis, and state management recommendations for senior developers.

Enables interaction with the Flutter SDK by providing tools to analyze and apply fixes to Dart and Flutter files.

A version-aware documentation MCP server for mobile development that verifies API availability against target platform versions.

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.

Enables cross-platform real device debugging for React Native development, supporting Android, iOS, and HarmonyOS with real-time connection status, screenshots, logs, diagnostics, evidence, and Codex context.

A minimal, secure MCP server for AI-assisted mobile development, enabling build, install, interact, and inspect Android/iOS apps.

MCP server that gives AI coding assistants the ability to see and interact with mobile devices. 49 tools for Android/iOS — AI-powered visual analysis (Claude + Gemini), smart tap/type by description, Flutter widget tree inspection, video recording, and test script generation. 4-tier element search with <1ms local matching. Free tier included, zero setup via npx.

Enables agents and LLMs to interact with native iOS and Android applications and devices via structured accessibility snapshots or coordinate-based taps, supporting simulators, emulators, and real devices.

Enables agents and LLMs to automate, inspect, and scrape native iOS and Android apps across simulators, emulators, and real devices through a platform-agnostic interface using accessibility snapshots or screenshot-based coordinates. It provides device, app, screen, input, log, and crash management tools, including optional cloud device reservation.

Integrates the Pub.dev API with AI assistants to provide real-time Flutter package information, documentation, and trend analysis. It enables users to search for packages, compare versions, and evaluate quality scores through natural language commands.

Enables mobile device automation for Android (via ADB) and iOS Simulator (via simctl), allowing you to control devices with natural language through screenshots, UI interactions, text input, and app management.