Flutter Driver MCP

Flutter Driver MCP

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

Category
Visit Server

README

πŸ§ͺ Flutter Driver MCP

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

Flutter Driver MCP bridges your LLM (Claude, Gemini, etc.) to a running Flutter application via Flutter's test framework + WebSocket, giving the agent full interactive control of the UI.

Now with screen recording! Record your app sessions as native video files (MP4/MOV) on iOS Simulators, macOS Desktop, and Android devices.


πŸ’‘ Why Flutter Driver MCP?

Zero-config injection. No changes to your app's source code. The harness is auto-injected at launch time β€” just point at a project path and go.

Focused, LLM-optimized toolset. 26 purpose-built tools instead of hundreds. Every tool description fits comfortably in an LLM context window without drowning the model in irrelevant options.

Suggestive errors. When a widget isn't found, the harness fuzzy-matches against the live widget tree and returns "Did you mean…?" suggestions β€” dramatically reducing agent retry loops and wasted tokens.

Token-efficient inspection. Widget tree output strips Dart generics, flattens layout boilerplate (Container, Padding, SizedBox…), and omits heavyweight coordinate data by default. The agent sees only what matters.

Full WidgetTester power. Every interaction runs through Flutter's real test framework with pumpAndSettle() after each action β€” no timing hacks, no flaky coordinate-based taps.

✨ What Can It Do?

Category Tools
Lifecycle start_app Β· stop_app Β· pilot_hot_restart Β· list_devices Β· start_recording Β· stop_recording
Interaction tap Β· enter_text Β· scroll Β· drag_and_drop Β· scroll_until_visible Β· wait_for Β· press_key
Inspection get_widget_tree Β· get_accessibility_tree Β· explore_screen Β· get_text Β· screenshot
Assertions assert
Navigation navigate_to Β· go_back Β· get_current_route
Environment simulate_background Β· set_network_status Β· intercept_network
Utilities read_logs Β· batch_actions Β· wait_for_animation

Unified Selectors

All interaction tools accept a simple target string instead of verbose JSON:

"#my_key"                    β†’  find by Key
"text=\"Submit\""              β†’  find by text
"type=\"Checkbox\""            β†’  find by widget type
"tooltip=\"Back\""             β†’  find by tooltip
"semanticsLabel=\"Username\""  β†’  find by semantics label (hint text, accessibility label)

Suggestive Errors

When a widget isn't found, the harness scans the tree and returns "Did you mean…?" suggestions β€” dramatically reducing agent retry loops.


πŸ— Architecture

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    JSON-RPC/stdio    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   WebSocket   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  MCP Client  β”‚ ◄──────────────────► β”‚  Node.js Server  β”‚ ──connects──► β”‚  Dart Harness    β”‚
β”‚  (LLM Agent) β”‚                      β”‚  (index.ts)      β”‚               β”‚  (harness.dart)  β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜                      β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜               β”‚  inside Flutter  β”‚
                                                                         β”‚  flutter_test    β”‚
                                                                         β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
  1. The Node.js MCP server receives tool calls from any MCP-compatible client.
  2. On start_app, it injects a Dart harness into the project's integration_test/ directory and launches flutter run --machine.
  3. The harness starts a WebSocket server inside the app. The Node server connects to it and sends JSON-RPC commands.
  4. All interactions (tap, scroll, assert, screenshot, etc.) execute inside the real Flutter test framework with full access to the widget tree.

Zero external dependencies. The harness only imports dart:* core libraries and package:flutter_test (already in every Flutter project). No changes to your pubspec.yaml, no entitlement edits, no setup steps.


πŸ“¦ Installation

You can run the server directly via npx in your MCP configuration without installing anything globally.

If you instead wish to install it globally:

npm install -g flutter-driver-mcp

Prerequisites

  • Node.js β‰₯ 18
  • Flutter SDK on your PATH
  • Any Flutter project β€” no additional dependencies or setup required

πŸš€ Usage

Claude Code

To add this server to Claude Code, run:

claude mcp add flutter-driver -- npx -y flutter-driver-mcp

Other MCP clients (Desktop, IDEs, etc.)

Add the following to your MCP client configuration:

{
  "mcpServers": {
    "flutter-driver": {
      "command": "npx",
      "args": ["-y", "flutter-driver-mcp"]
    }
  }
}

Quick start

Once your MCP client is connected, just tell the agent what you want β€” it'll figure out the tools:

"Launch my app at /path/to/my_app on macOS and test the login flow"

"Verify the account creation flow is working"

"Take a screenshot and verify the home screen loaded"

The agent handles start_app, explore_screen, tap, assert, screenshot, etc. automatically. No need to spell out tool calls.


πŸ”§ Tool Reference

Lifecycle

Tool Description
start_app Injects the harness, launches the app via flutter run, and connects over WebSocket. Surfaces actual build errors (compiler messages, Xcode failures) instead of generic timeouts.
stop_app Gracefully sends app.stop to the Flutter daemon, kills processes, and cleans up. Auto-stops any active recording.
pilot_hot_restart Sends a full restart command to the running app (preserves session).
list_devices Lists available Flutter devices (simulators, emulators, physical, desktop). No running app required.
start_recording Starts recording the screen of the running app's device. Supports iOS Simulators (MP4), macOS Desktop (MOV), and Android (MP4, max 180s). Auto-stops after 5 minutes or on stop_app.
stop_recording Stops the current recording and finalizes the video file. Returns the file path, format, duration, and size. Called automatically by stop_app if a recording is active.

Interaction

Tool Description
tap Taps, long-presses, or double-taps a widget. Set gesture: "long_press" or gesture: "double" to change behavior. Defaults to a normal tap. Automatically scrolls it into view first.
enter_text Enters text into a TextField. Supports finding fields by hint text via semanticsLabel="Hint". Set clearFirst: true to explicitly clear the field before typing. Optionally sends a TextInputAction (e.g. done, search).
scroll Scrolls or swipes a widget. Use dx/dy for pixel-precise scrolling, or direction (up/down/left/right) + optional distance for named swipe gestures.
drag_and_drop Drags from a source widget to a destination widget or custom pixel offset.
scroll_until_visible Scrolls a scrollable container until a target widget appears.
wait_for Polls until a widget appears (with timeout). Set gone: true to wait for disappearance instead (e.g. loading spinners).
press_key Simulates a keyboard key press (enter, tab, escape, backspace, arrow keys, etc.).

Inspection

Tool Description
get_widget_tree Returns the full widget tree as JSON. Use summaryOnly: true to filter layout noise.
get_accessibility_tree Returns the Semantics tree β€” compact, labels-focused, ideal for LLMs. Pass includeRect: true if coordinates are needed.
explore_screen Maps all interactive elements on the current screen using the native Semantics tree. Each element includes a suggestedTarget β€” a copy-pasteable selector string guaranteed to work with interaction tools.
get_text Returns the raw text string from a widget (supports Text, EditableText, and RichText descendants).
screenshot Captures a PNG screenshot. Without a target, captures the full app (defaults to type: "app"). With a target, captures that specific widget.

Assertions

Tool Description
assert Runs an assertion on a widget. Use check to specify the type: exists, not_exists, text_equals (with expected), text_contains (substring match with expected), count (with expected integer), state (with stateKey + expected), visible, or enabled (with expected).

Navigation & Environment

Tool Description
navigate_to Pushes a named route via Navigator.pushNamed. Does NOT work with GoRouter or other custom routers β€” use tap() to navigate via on-screen elements instead.
go_back Pops the current route or dismisses modal overlays (bottom sheets, dialogs). Falls back to Escape key for overlays that aren't Navigator routes.
get_current_route Returns the name of the currently active route β€” lets the agent know where it is.
simulate_background Sends the app to background and brings it back after a duration.
set_network_status Toggles WiFi on/off (macOS/iOS Simulator only).
intercept_network Registers a mock HTTP response for a URL pattern. Pass null to clear.

Utilities

Tool Description
read_logs Returns the last N lines from the app's stdout/stderr.
batch_actions Executes multiple actions in a single tool call (e.g. fill a form: 5Γ— enter_text + tap). Runs sequentially with pumpAndSettle between each.
wait_for_animation Waits for all animations to finish before proceeding.

🀝 Using with the Official Dart/Flutter MCP Server

Flutter Driver MCP is complementary to the official Dart/Flutter MCP server. While there is some overlap in app interaction (like widget tree inspection), they serve distinct roles in a developer's workflow:

Feature Official Dart MCP Flutter Driver MCP
Primary Focus IDE productivity, code analysis & linting Live AI-Driven E2E Testing
Connectivity Dart Tooling Daemon (DTD) WebSocket to Injected Harness
App Control Hot reload/restart, workspace symbols Mocking, backgrounding, network interception
AI Discovery Widget Tree (standard) Semantics-first (explore_screen)
Assertions Manual tree inspection by agent On-device assertions (assert with check parameter)
Key Tools dart_fix, analyze_files, run_tests, pub tap, explore_screen, assert, intercept_network

Use both together: the official server for deep code analysis, package management, and standard IDE features; use Flutter Driver MCP when you need the agent to live-test the app UI, simulate complex environment states, and verify behavior with high-level assertions.

Agent Instructions (Copy & Paste)

If you're using both servers in the same project, drop the following into your project's AGENTS.md (or equivalent instruction file) so your AI agent knows when to reach for which:

<details> <summary>πŸ“‹ Click to expand dual-server agent instructions</summary>

## MCP Server Usage Guide

This project has two MCP servers. Use the right one for the job:

### Official Dart/Flutter MCP Server
Use for **code-level** work β€” things you'd do in an IDE:
- Adding/removing packages (`pub add`, `pub remove`)
- Resolving symbols, finding definitions (`resolve_workspace_symbol`, `hover`)
- Running unit/widget tests (`run_tests`)
- Static analysis and formatting (`analyze_files`, `dart_fix`, `dart_format`)
- Hot reload/restart via DTD (`hot_reload`, `hot_restart`)
- Reading package source code (`read_package_uris`)

### Flutter Driver MCP Server
Use for **live UI** work β€” things a real user would do:
- Launching the app on a device (`list_devices`, `start_app`)
- Tapping, typing, scrolling, swiping, dragging (`tap` with `gesture`, `enter_text`, `scroll` with `direction`, `drag_and_drop`, `press_key`)
- Checking what's on screen (`explore_screen`, `get_widget_tree`, `screenshot`, `get_text`)
- Asserting UI state (`assert` with `check`: `exists`, `not_exists`, `text_equals`, `text_contains`, `count`, `state`, `visible`, `enabled`)
- Mocking network responses (`intercept_network`)
- Navigating (`navigate_to`, `go_back`, `get_current_route`)
- Simulating environment (`simulate_background`, `set_network_status`)
- Executing scoped waits (`wait_for` with `gone` flag)

### Key Rules
- **Hot restart**: Use `pilot_hot_restart` if the app was started via Driver's `start_app`.
  Use the official `hot_restart` if working through DTD. Never mix them.
- **Optimal workflow**: Use the Official server to edit code β†’ `pilot_hot_restart` to refresh β†’
  Driver's `explore_screen` or `assert_exists` to verify the change rendered correctly.
- After any Driver interaction (`tap`, `enter_text`, etc.), the harness automatically
  calls `pumpAndSettle()`. You don't need manual waits unless testing async network latency.

</details>


πŸ§ͺ Running Tests

The project includes comprehensive verification scripts:

# Build (includes Dart syntax verification)
npm run build

# Run the full integration test suite
npm run verify-integration

The integration tests boot a real Flutter app (test_app/), exercise all major tools over JSON-RPC, and verify correct behavior.


πŸ“„ License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured