MCP App UI Builder
PROCreate MCP Apps with interactive UI components like dashboards, forms, and data visualizations that render directly inside AI assistant conversations.
Example Usage
Build an MCP App for a project management dashboard:
Requirements:
- Dashboard with task boards (Kanban-style columns: To Do, In Progress, Done)
- Interactive forms for creating and editing tasks
- Data visualization: burndown chart showing sprint progress
- Multi-step workflow: Sprint planning wizard (set goals → assign tasks → review capacity)
- Data source: REST API at https://api.example.com/projects
- Authentication: Bearer token from environment variable
The dashboard should:
- Show real-time task counts per status
- Allow drag-and-drop between columns (or button-based move)
- Display a line chart for burndown tracking
- Support dark mode
- Include error states and loading indicators
Generate the complete MCP server with all UI components, API integration, and state management.
Skill Prompt
This skill works best when copied from findskill.ai — it includes variables and formatting that may not transfer correctly elsewhere.
How to Use This Skill
1
Copy the skill using the button above
2
Paste into your AI assistant (Claude, ChatGPT, etc.)
3
Fill in your inputs below (optional) and copy to include with your prompt
4
Send and start chatting with your AI
Suggested Customization
| Description | Default | Your Value |
|---|---|---|
| Type of MCP App to create: dashboard, form, data-visualization, wizard, crud-interface, or custom | dashboard | |
| Primary data source: API endpoint, database, file system, in-memory, or external service | API endpoint | |
| UI approach: MCP UI components (standard), custom HTML/CSS, or React (for complex apps) | MCP UI components | |
| Interaction level: read-only (display data), basic (buttons/links), full interactive (forms, drag-drop, real-time) | full interactive |
- Copy the skill above and paste it into Claude Code or your preferred AI assistant
- Describe the MCP App you want to build: what data to display, what interactions to support, and your data source
- Review the generated MCP server code, UI components, and state management
- Install the MCP SDK:
npm install @modelcontextprotocol/sdk - Run your MCP server and add it to your AI client configuration
- Test the interactive UI inside your AI conversations
What You’ll Get
- Complete MCP server with tool handlers that return interactive UI
- Dashboard, form, chart, and Kanban board component templates
- Dark mode support with CSS custom properties
- State management with persistence (SQLite or file-based)
- API integration patterns with error handling
- Loading, empty, and error state components
- Testing setup with Vitest
- npm packaging and deployment configuration
Tips for Best Results
- Start with a simple dashboard and add interactivity incrementally
- Keep component HTML under 50KB for best rendering performance
- Always include text fallback content alongside UI components
- Test with Claude Desktop to verify interactive rendering
- Use CSS custom properties for theming so dark mode works automatically
Research Sources
This skill was built using research from these authoritative sources:
- MCP Blog: Introducing MCP Apps Official announcement of MCP Apps with interactive UI capabilities, architecture overview, and component reference
- Model Context Protocol Specification Full MCP specification including tool definitions, resource management, and the Apps UI rendering protocol
- Anthropic MCP Documentation Anthropic's guide to building MCP servers with TypeScript and Python, including deployment and configuration
- Generect: Complete Guide to MCP Comprehensive tutorial covering MCP architecture, server implementation, tool design, and real-world use cases
- Intuz: Building MCP Servers for AI Agents Enterprise-focused guide to MCP server development with authentication, scaling, and production deployment patterns
- MCP TypeScript SDK Official TypeScript SDK for building MCP servers and clients with examples and API reference