Budget Allocator

An interactive budget allocation tool demonstrating real-time data visualization with MCP Apps.

MCP Client Configuration

Add to your MCP client configuration (stdio transport):

{
  "mcpServers": {
    "budget-allocator": {
      "command": "npx",
      "args": [
        "-y",
        "--silent",
        "--registry=https://registry.npmjs.org/",
        "@modelcontextprotocol/server-budget-allocator",
        "--stdio"
      ]
    }
  }
}

Local Development

To test local modifications, use this configuration (replace ~/code/ext-apps with your clone path):

{
  "mcpServers": {
    "budget-allocator": {
      "command": "bash",
      "args": [
        "-c",
        "cd ~/code/ext-apps/examples/budget-allocator-server && npm run build >&2 && node dist/index.js --stdio"
      ]
    }
  }
}

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:

   npm install
   

2. Build and start the server:

   npm run start:http  # for Streamable HTTP transport
   # OR
   npm run start:stdio  # for stdio transport
   

3. View using the 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.ui.resourceUri.

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