Add budget-allocator-server example

Demo MCP App for interactive budget allocation with:
- Slider controls for 5 categories (Marketing, Engineering, etc.)
- Real-time donut chart visualization via Chart.js
- 24-month sparkline trends per category
- Industry benchmark percentile badges
- Company stage selector (Seed through Growth)
- Budget preset buttons ($50K-$500K)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

examples/budget-allocator-server/README.md

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+# Example: Budget Allocator App
+
+An interactive budget allocation tool demonstrating real-time data visualization with MCP Apps.
+
+## Features
+
+- **Interactive Sliders**: Adjust budget allocation across 5 categories (Marketing, Engineering, Operations, Sales, R&D)
+- **Donut Chart**: Real-time visualization of allocation distribution using Chart.js
+- **Sparkline Trends**: 24-month historical allocation data per category
+- **Percentile Badges**: Compare your allocation vs. industry benchmarks
+- **Stage Selector**: Switch between Seed, Series A, Series B, and Growth benchmarks
+- **Budget Presets**: Quick selection of $50K, $100K, $250K, or $500K totals
+
+## Running
+
+1. Install dependencies:
+
+   ```bash
+   npm install
+   ```
+
+2. Build and start the server:
+
+   ```bash
+   npm start
+   ```
+
+   The server will listen on `http://localhost:3001/mcp`.
+
+3. View using the [`basic-host`](https://github.com/modelcontextprotocol/ext-apps/tree/main/examples/basic-host) example or another MCP Apps-compatible host.
+
+## Architecture
+
+### Server (`server.ts`)
+
+Exposes a single `get-budget-data` tool that returns:
+
+- Category definitions with colors and default allocations
+- Historical data (~120 data points) - 24 months of allocation history per category
+- Industry benchmarks (~60 data points) - Aggregated percentile data by company stage
+
+The tool is linked to a UI resource via `_meta[RESOURCE_URI_META_KEY]`.
+
+### App (`src/mcp-app.ts`)
+
+- Uses Chart.js for the donut chart visualization
+- Renders sparkline trends using inline SVG
+- Computes percentile rankings client-side from benchmark data
+- Updates all UI elements reactively on slider changes