Devcon Workshop 2026

---

📌 Overview

This project implements a Model Context Protocol (MCP) server with support for:

• Tool exposure for LLM clients (e.g., VS Code Copilot)
• External API integration
• Autodesk Platform Services (APS) connectivity
• Authentication flows (2-legged & 3-legged OAuth)
• Custom client + agent architecture

It represents a production-oriented agentic AI backend system.

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🧠 Architecture

🔷 High-Level Flow

+------------------------+
| LLM Client (VSCode)    |
| Copilot / Chat UI      |
+-----------+------------+
            |
            v
+------------------------+
| MCP Server             |
| (server.js / aps)      |
+-----------+------------+
            |
------------------------------------------------
      |                |                |
      v                v                v
+-------------+ +-------------+ +----------------+
| External    | |   APS APIs  | |  Custom Logic  |
| APIs        | | (OAuth)     | |   / Tools      |
+-------------+ +-------------+ +----------------+

---

🔷 Agent Flow

User Prompt
↓
LLM decides tool
↓
MCP Server executes tool
↓
External API / APS call
↓
Structured response → LLM → User

---

📁 Project Structure

├── .vscode/
│ └── mcp.json # MCP configuration for VS Code client
│
├── node_modules/ # Installed dependencies
│
├── .env # Environment variables (API keys, secrets)
├── .gitignore # Git ignored files
│
├── agent.js # Agent logic (tool orchestration)
├── aps-server.js # APS integration server (OAuth + APIs)
├── client.js # Custom MCP client implementation
├── server.js # Core MCP server (tool definitions)
│
├── package.json # Project metadata & dependencies
├── package-lock.json # Dependency lock file

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⚙️ Tech Stack

• Node.js (ES Modules)
• Model Context Protocol (MCP SDK)
• Zod (schema validation)
• HTTP Streaming Transport
• Autodesk Platform Services (APS)

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🔑 Key Components

1. server.js

• Core MCP server
• Registers tools
• Handles client requests

---

2. aps-server.js

• Integrates Autodesk APIs
• Handles OAuth (2L + 3L)
• Secure API communication

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3. agent.js

• Implements agentic behavior
• Decides which tools to call
• Enables multi-step workflows

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4. client.js

• Custom MCP client
• Can simulate or replace VS Code client

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5. .vscode/mcp.json

• Connects VS Code → MCP server

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🚀 Getting Started

1️⃣ Install Dependencies

npm install

2️⃣ Setup Environment

Create .env file:

PORT=3000

# APS Credentials
APS_CLIENT_ID=your_client_id
APS_CLIENT_SECRET=your_client_secret

# External APIs
GEMINI_API_KEY=your_key

3️⃣ Run Server

node server.js

Expected output:

MCP server running at http://localhost:3000/mcp

4️⃣ Configure VS Code

Create:

.vscode/mcp.json

{
  "servers": {
    "devcon-workshop": {
      "type": "http",
      "url": "http://localhost:3000/mcp"
    },
    "devcon-aps": {
      "type": "http",
      "url": "http://localhost:3001/mcp"
    }
  }
}

5️⃣ Test Tools

In Copilot Chat:

#add 10 and 20
#greet John in spanish
What's the weather in London?

🧩 Tool Design Pattern

server.registerTool(
"tool_name",
{
description: "Tool description",
inputSchema: {
param: z.string()
}
},
async ({ param }) => ({
content: [{ type: "text", text: "Result" }]
})
);

---

🔐 Authentication

✅ 2-Legged OAuth

Server-to-server

No user interaction

✅ 3-Legged OAuth

User consent required

Fine-grained permissions

Recommended for production

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🏗️ Production Considerations

🔹 Scalability

Stateless architecture

Horizontal scaling possible

🔹 Security

Use .env for secrets

Prefer 3LO for user data

🔹 Reliability

Input validation (Zod)

Structured responses

🔹 Observability Add logging for tool execution

Monitor API failures

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🎯 Features

✔ MCP-compliant server

✔ External API integration

✔ APS connectivity

✔ Agent-based execution

✔ Custom client support

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🔮 Future Enhancements

Dockerize the application

Deploy on Azure / AWS

Add database-backed tools

Implement caching layer

📜 License

MIT License

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🙌 Acknowledgements

• Autodesk Platform Services (APS)
  https://autodesk-platform-services.github.io/mcp-devcon2026/

• Model Context Protocol (MCP)

• OpenAI / LLM ecosystem