ext-apps/examples/customer-segmentation-server/README.md
Olivier Chafik 298e884ec3
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# Example: Customer Segmentation Explorer
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.
<table>
<tr>
<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>
<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>
<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>
</tr>
</table>
## MCP Client Configuration
Add to your MCP client configuration (stdio transport):
```json
{
"mcpServers": {
"customer-segmentation": {
"command": "npx",
"args": [
"-y",
"--silent",
"--registry=https://registry.npmjs.org/",
"@modelcontextprotocol/server-customer-segmentation",
"--stdio"
]
}
}
}
```
### Local Development
To test local modifications, use this configuration (replace `~/code/ext-apps` with your clone path):
```json
{
"mcpServers": {
"customer-segmentation": {
"command": "bash",
"args": [
"-c",
"cd ~/code/ext-apps/examples/customer-segmentation-server && npm run build >&2 && node dist/index.js --stdio"
]
}
}
}
```
## Features
- **Interactive Scatter Plot**: Bubble chart visualization using Chart.js with configurable X/Y axes
- **Segment Clustering**: 250 customers grouped into 4 segments (Enterprise, Mid-Market, SMB, Startup)
- **Axis Selection**: Choose from 6 metrics for each axis (Revenue, Employees, Account Age, Engagement, Tickets, NPS)
- **Size Mapping**: Optional bubble sizing by a third metric for additional data dimension
- **Legend Filtering**: Click segment pills to show/hide customer groups
- **Detail Panel**: Hover or click customers to see name, segment, revenue, engagement, and NPS
- **Theme Support**: Adapts to light/dark mode preferences
## Running
1. Install dependencies:
```bash
npm install
```
2. Build and start the server:
```bash
npm run start:http # for Streamable HTTP transport
# OR
npm run start:stdio # for stdio transport
```
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-customer-data` tool that returns:
- Array of 250 generated customer records with segment assignments
- Segment summary with counts and colors for each group
- Optional segment filter parameter
The tool is linked to a UI resource via `_meta.ui.resourceUri`.
### App (`src/mcp-app.ts`)
- Uses Chart.js bubble chart for the visualization
- Fetches data once on connection
- Dropdown controls update chart axes and bubble sizing
- Custom legend with clickable segment toggles
- Detail panel updates on hover/click interactions
### Data Generator (`src/data-generator.ts`)
- Generates realistic customer data with Gaussian clustering around segment centers
- Each segment has characteristic ranges for revenue, employees, engagement, etc.
- Company names generated from word-list combinations (e.g., "Apex Data Corp")
- Data cached in memory for consistency across requests