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MCP Server + Flutter MCP Toolkit

@Arenukvern

Basic information

Category

Developer Tools

License

MIT

Transports

stdio

Author

Arenukvern

Submitted by

Anton Malofeev

About 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.

MCP Server + Flutter MCP Toolkit config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

MCP Server + Flutter MCP Toolkit tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

1

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.

2

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.

3

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.

4

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.

5

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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