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Digital Twin MCP Server

by aisystant
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JavaScript
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Digital Twin MCP Server

Тип репозитория: DS/instrument

MCP (Model Context Protocol) server for Digital Twin learner data. Provides tools for AI Guide (Проводник) to work with learner profiles based on 4-type indicator classification.

Overview

This server implements a metamodel-driven approach with 3 MCP tools and 4 indicator types (IND.1-4).

Key Features

  • 3 MCP Tools for metamodel exploration and data management

  • 4-Type Classification (IND.1-4) with access control

  • 65+ Indicators organized in hierarchical structure

  • Dual Deployment - stdio for local MCP clients + HTTP API for Cloudflare Workers

Related MCP server: Chen's AI Copy

Architecture

┌─────────────────────────────────────┐
│  AI Guide (LLM with MCP client)     │
│  - Analyzes learner state           │
│  - Calls MCP tools                  │
│  - Provides guidance                │
└──────────────┬──────────────────────┘
               │
               ▼
┌─────────────────────────────────────┐
│  MCP Server (this project)          │
│  - 3 tools                          │
│  - Access control (IND.1 writable)  │
│  - Metamodel-driven                 │
└──────────────┬──────────────────────┘
               │
               ▼
┌─────────────────────────────────────┐
│  Data Store                         │
│  - Metamodel (MD files)             │
│  - Twin data (PostgreSQL/Neon)      │
│  - OAuth state (Cloudflare KV)      │
└─────────────────────────────────────┘

Available Tools

Tool

Description

describe_by_path

Navigate metamodel structure. List categories, groups, indicators

read_digital_twin

Read data from digital twin by path

write_digital_twin

Write data to digital twin (1_declarative only for users)

Installation

Prerequisites

  • Node.js 18+

  • npm or yarn

  • Cloudflare account (for deployment)

  • Neon PostgreSQL database (for persistent twin data storage)

Install Dependencies

npm install

Usage

Option 1: Local MCP Server (stdio)

For use with MCP clients like Claude Desktop:

node src/index.js

Add to your MCP client configuration:

{
  "mcpServers": {
    "digital-twin": {
      "command": "node",
      "args": ["/path/to/digital-twin-mcp/src/index.js"]
    }
  }
}

Option 2: Cloudflare Workers (HTTP API)

Local Development

npm run dev

This starts the development server at http://localhost:8787

Test Endpoints

# Health check
curl http://localhost:8787/

# List all tools
curl http://localhost:8787/tools

# Describe metamodel root
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "describe_by_path",
    "arguments": {"path": "/"}
  }'

Deploy to Cloudflare

Uses Cloudflare GitHub App for automatic deployment on push to main.

Set secrets before first deploy:

npx wrangler secret put ORY_CLIENT_SECRET --env ory-auth
npx wrangler secret put DATABASE_URL --env ory-auth

Manual deployment:

npm run deploy -- --env ory-auth

API Examples

Explore Metamodel

# List all categories
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "describe_by_path", "arguments": {"path": "/"}}'

# List subgroups in 1_declarative
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "describe_by_path", "arguments": {"path": "1_declarative"}}'

# List indicators in goals subgroup
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "describe_by_path", "arguments": {"path": "1_declarative/1_2_goals"}}'

# Read specific indicator definition
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "describe_by_path", "arguments": {"path": "1_declarative/1_2_goals/09_Цели обучения"}}'

Read Twin Data

# Read all data
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "read_digital_twin", "arguments": {"path": "/"}}'

# Read specific path
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{"tool": "read_digital_twin", "arguments": {"path": "indicators.agency"}}'

Write Twin Data

# Write to 1_declarative (allowed)
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "write_digital_twin",
    "arguments": {
      "path": "1_declarative/goals/learning",
      "data": ["Learn TypeScript", "Master MCP"]
    }
  }'

# Write to 2_collected (denied for users)
curl -X POST http://localhost:8787/call \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "write_digital_twin",
    "arguments": {
      "path": "2_collected/time/total",
      "data": 100
    }
  }'
# Returns: {"error": "Access denied: users cannot write to 2_collected"}

Testing

Run tests:

npm test

Test stdio server directly:

echo '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | node src/index.js

Development

Project Structure

digital-twin-mcp/
├── src/
│   ├── index.js              # MCP server (stdio, file-based storage)
│   ├── worker-sse.js         # Cloudflare Worker (PostgreSQL/Neon storage)
│   └── metamodel-data.js     # Generated metamodel data
├── metamodel/                # MD files defining indicators
├── data/
│   └── twin.json             # Twin data store (stdio mode only)
├── scripts/
│   └── build-metamodel.js    # Regenerate metamodel-data.js
├── package.json
├── wrangler.toml             # Cloudflare config
└── README.md

Adding New Indicators

  1. Determine type (IND.1-4)

  2. Place MD file in correct category/subgroup folder

  3. Use format: NN_Name.md

  4. Include required metadata:

    # IND.X.Y.Z

**Name:** Indicator name
**Name (EN):** English name
**Type:** semantic|temporal|categorical
**Format:** string|float|enum|structured_text

  5. Regenerate data: node scripts/build-metamodel.js

  6. Run tests: npm test

Related Documentation

License

MIT

Version: 2.0.0 Last Updated: 2025-02-05

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