MCP Server + Flutter MCP Toolkit

@Arenukvern

代码仓库主页

基本信息

分类

开发工具

许可证

MIT

传输方式

stdio

作者

Arenukvern

提交者

Anton Malofeev

关于 MCP Server + Flutter MCP Toolkit

MCP Toolkit for Flutter AI Agent Driven Development (MCP/CLI + custom client side tools) - via closed feedback loop (visual & semantic snapshot) and high client side customization adaptable for any Flutter app. Nowadays it is often called as agentic harness.

#dart #mcp #flutter #mcp-server

MCP Server + Flutter MCP Toolkit 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Server + Flutter MCP Toolkit 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Flutter MCP Toolkit?

Flutter MCP Toolkit is a Dart MCP server and Flutter package that lets AI agents (Claude Code, Codex, Cursor, and others) inspect and drive a running Flutter app through semantic snapshots, widget interaction, hot-reload, log reading, and runtime custom tool registration.

How to use Flutter MCP Toolkit?

Install the binary via curl, add the toolkit to your Flutter app with flutter-mcp-toolkit codegen-init, install agent skills with flutter-mcp-toolkit init <agent>, then run your app with flutter run --debug.

Key features of Flutter MCP Toolkit

30 MCP tools under the fmt_* capability prefix across four categories
Dynamic Tools Registration for apps to create custom tools at runtime
Supports inspection, interaction, debug, and lifecycle operations
Works with multiple AI agents including Claude Code, Codex, and Cursor
Flutter apps can expose custom MCP tools and resources at runtime

Use cases of Flutter MCP Toolkit

An AI assistant inspecting widget state, tapping buttons, and typing into forms in a running Flutter app
A closed feedback loop where the AI hot-reloads code, verifies changes, and iterates without leaving the conversation
A Flutter app registering its own domain-specific MCP tools at runtime for the AI agent to use

常见问题

How does this differ from the official MCP Server for Flutter?

The official server exposes Dart tooling; this project focuses on dynamic MCP tools registration from within the Flutter app and a close feedback loop for AI agents.

What are the runtime requirements?

Flutter 3.44 or later. The Flutter app must be running in debug mode. The MCP server binary is shipped via GitHub Releases.

Are there any known limitations?

Dump RPC methods (e.g., `dump_render_tree`) can produce large token output and are disabled by default; enable them with the `--dumps` flag.

How is security handled?

The server connects to a Flutter app in debug mode only. It has been verified by MseeP.ai. Review the ARCHITECTURE.md for details on potential modifications for improved security.

Which AI agents are supported?

Claude Code, Codex, Cursor, Intent, Cline, and others. Use `flutter-mcp-toolkit init <agent>` or `npx skills add Arenukvern/mcp_flutter -a <agent>` to install skills.

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