@modelcontextprotocol/server-customer-segmentation

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.

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

• Install dependencies:

  npm install
  

• Build and start the server:

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

• View using the 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