cce8d5c7a3Add stdio transport configuration snippets near the top of each example README to help users quickly set up the servers in their MCP clients. - Node.js examples use npx with the published npm packages - Python qr-server uses uv with local path - Removed Claude Desktop-specific references from qr-server
87 lines
3.5 KiB
Markdown
87 lines
3.5 KiB
Markdown
# Example: Customer Segmentation Explorer
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A demo MCP App that displays customer data as an interactive scatter/bubble chart with segment-based clustering. Users can explore different metrics, filter by segment, and click to see detailed customer information.
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<table>
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<tr>
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<td><a href="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/01-account-age-revenue.png"><img src="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/01-account-age-revenue.png" alt="Account age vs revenue" width="100%"></a></td>
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<td><a href="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/02-tickets-nps-engagement.png"><img src="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/02-tickets-nps-engagement.png" alt="Tickets, NPS, engagement" width="100%"></a></td>
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<td><a href="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/07-age-engagement-revenue.png"><img src="https://modelcontextprotocol.github.io/ext-apps/screenshots/customer-segmentation-server/07-age-engagement-revenue.png" alt="Age, engagement, revenue" width="100%"></a></td>
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</tr>
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</table>
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## MCP Client Configuration
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Add to your MCP client configuration (stdio transport):
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```json
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{
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"mcpServers": {
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"customer-segmentation": {
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"command": "npx",
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"args": [
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"-y",
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"--silent",
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"--registry=https://registry.npmjs.org/",
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"@modelcontextprotocol/server-customer-segmentation",
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"--stdio"
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]
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}
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}
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}
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```
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## Features
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- **Interactive Scatter Plot**: Bubble chart visualization using Chart.js with configurable X/Y axes
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- **Segment Clustering**: 250 customers grouped into 4 segments (Enterprise, Mid-Market, SMB, Startup)
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- **Axis Selection**: Choose from 6 metrics for each axis (Revenue, Employees, Account Age, Engagement, Tickets, NPS)
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- **Size Mapping**: Optional bubble sizing by a third metric for additional data dimension
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- **Legend Filtering**: Click segment pills to show/hide customer groups
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- **Detail Panel**: Hover or click customers to see name, segment, revenue, engagement, and NPS
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- **Theme Support**: Adapts to light/dark mode preferences
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## Running
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1. Install dependencies:
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```bash
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npm install
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```
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2. Build and start the server:
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```bash
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npm run start:http # for Streamable HTTP transport
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# OR
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npm run start:stdio # for stdio transport
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```
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3. View using the [`basic-host`](https://github.com/modelcontextprotocol/ext-apps/tree/main/examples/basic-host) example or another MCP Apps-compatible host.
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## Architecture
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### Server (`server.ts`)
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Exposes a single `get-customer-data` tool that returns:
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- Array of 250 generated customer records with segment assignments
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- Segment summary with counts and colors for each group
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- Optional segment filter parameter
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The tool is linked to a UI resource via `_meta.ui.resourceUri`.
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### App (`src/mcp-app.ts`)
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- Uses Chart.js bubble chart for the visualization
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- Fetches data once on connection
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- Dropdown controls update chart axes and bubble sizing
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- Custom legend with clickable segment toggles
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- Detail panel updates on hover/click interactions
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### Data Generator (`src/data-generator.ts`)
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- Generates realistic customer data with Gaussian clustering around segment centers
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- Each segment has characteristic ranges for revenue, employees, engagement, etc.
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- Company names generated from word-list combinations (e.g., "Apex Data Corp")
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- Data cached in memory for consistency across requests
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