DynamicAgent2UI
Enables AI agents to render native-looking floating dialogs and forms on the user's desktop, capturing user interactions like button clicks and form inputs.
README
DynamicAgent2UI 🖥️🤖
An OS-Native Floating Dialog & Form UI Canvas that exposes interactive desktop widgets to AI agents using the Model Context Protocol (MCP).
With DynamicAgent2UI, any MCP-compatible AI agent (such as Gemini Antigravity, Claude Desktop, or VS Code Cline) can render high-fidelity, native-looking dialogs and settings forms directly on the user's desktop screen, block execution, and retrieve the user's interaction (button clicks, form inputs) as the tool response.
✨ Features
- 🖥️ OS-Native Styles: Renders native-looking dialogs and forms matching macOS, Windows 11 (Fluent), and Android (Material 3).
- 📐 Dynamic Window Resizing: Utilizes
ResizeObserverand Electron IPC to resize the frameless window to the exact dimensions of the dialog content (+ drop shadow padding), allowing clicks on transparent areas to pass through to background apps. - 🕳️ Opacity Correction: Uses solid, opaque fills (
bg-white&bg-[#1e1e1e]) preventing desktop wallpapers from bleeding through and keeping text/controls highly legible. - 🎛️ Draggable Regions: Allows the user to click and drag the dialog background to position it anywhere on their screen, while keeping buttons and inputs interactive.
- 🔌 Unified Self-Starting MCP: The MCP server automatically checks port
3000and launches the Next.js backend and Electron app in the background when the agent connects. Zero manual CLI commands required!
🛠️ Tech Stack
- Frontend: Next.js (App Router, Tailwind CSS, TypeScript, Zod)
- Desktop Wrapper: Electron (Frameless, Transparent, IPC, Node Integration)
- Protocol: Model Context Protocol (MCP JSON-RPC 2.0 over
stdio)
🚀 Getting Started
1. Prerequisites
- Node.js (v18 or higher recommended)
- npm (or pnpm/yarn)
2. Installation & Environment Configuration
Clone the repository, enter the directory, and install dependencies:
git clone https://github.com/your-username/DynamicAgent2UI.git
cd DynamicAgent2UI
npm install
Create a .env file in the root directory to configure the AI agent's chat interface (optional):
# Optional: Setup a custom LLM endpoint (OpenAI compatible) for the built-in control panel chat
CUSTOM_LLM_BASE_URL=https://api.your-provider.com/v1
CUSTOM_LLM_API_KEY=your-api-key
CUSTOM_LLM_MODEL=your-model-name
🔌 Using with an MCP Client (e.g. Gemini, Claude Desktop, Cline)
To integrate DynamicAgent2UI with your agent, add it to your client's MCP configuration settings file (e.g., claude_desktop_config.json or cline_mcp_settings.json):
{
"mcpServers": {
"DynamicAgent2UI": {
"command": "node",
"args": ["C:/Workspace/OpenUI/mcp-server.js"]
}
}
}
Note: Replace the absolute path in args with your cloned repository path.
Once configured and restarted, the agent will have access to the following tools:
Tool: show_dialog
Displays a native OS dialog and blocks until a button is clicked.
primaryButton(required): Text label (e.g."OK","Save").secondaryButton/cancelButton(optional): Alternative button labels.title/message(optional): Title and body description.icon(optional):"info" | "warning" | "error" | "question" | "success".platform(optional):"macos" | "windows" | "android". Defaults to auto-detecting the host OS.theme(optional):"light" | "dark". Default is"light".inputPlaceholder(optional): Adds a text input box.
Tool: show_form
Displays a native multi-input form panel.
title(required): Form header title.fields(required): Comma-separated labels and types, e.g."Username: text, Age: number, Role: select(Admin|User), Active: checkbox".submitButton(required): Button label.platform/theme(optional): OS style and color theme.
🏃 Running Manually (Optional)
If you wish to run the web interface or desktop window manually without the MCP server:
- Run the Next.js development server:
npm run dev - Run the Electron desktop window:
npm run desktop - Build for production:
npm run build
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.