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Getting Started: Adding Windows APIs to Your Electron App

This guide walks you through adding Windows-native capabilities to an Electron application using the Windows App Development CLI. You'll learn how to call modern Windows APIs from your Electron app, test with app identity, and package for distribution.

What You'll Build

By the end of this guide, you'll have an Electron app that:

  • ✅ Calls modern Windows APIs (Windows SDK and Windows App SDK)
  • ✅ Uses a native addon with AI capabilities (Phi Silica or WinML)
  • ✅ Runs with app identity for testing protected APIs
  • ✅ Packages as a signed MSIX for distribution

Prerequisites

Before starting, ensure you have:

  • Windows 11 (Copilot+ PC if using Phi Silica)
  • Node.js - winget install OpenJS.NodeJS --source winget
  • .NET SDK v10 - winget install Microsoft.DotNet.SDK.10 --source winget
  • Visual Studio with the Native Desktop Workload - winget install --id Microsoft.VisualStudio.Community --source winget --override "--add Microsoft.VisualStudio.Workload.NativeDesktop --includeRecommended --passive --wait"

The Process

Building a Windows-enabled Electron app involves three main phases:

1. Setting Up the Development Environment

First, you'll set up your development environment with the necessary tools and SDKs. This includes:

  • Creating or configuring an Electron app
  • Installing winapp CLI
  • Initializing Windows SDKs and required assets
  • Setting up your build pipeline

Get Started with Setup →

2. Creating a Native Addon

Next, you'll create a native addon that calls Windows APIs. Choose one of the following guides:

Option A: Creating a C++ Notification Addon

Learn how to create a C++ addon that calls the Windows App SDK notification APIs. This is a great starting point for understanding native addons before diving into more complex scenarios.

Create a C++ Notification Addon →

Option B: Creating a Phi Silica Addon

Learn how to create a C# addon that uses the Phi Silica AI model to summarize text on-device. Phi Silica is a small language model that runs locally on Windows 11 devices with NPUs.

Create a Phi Silica Addon →

Option C: Creating a WinML Addon

Learn how to create a C# addon that uses Windows Machine Learning (WinML) to run custom ONNX models for image classification, object detection, and more.

Create a WinML Addon →

3. Packaging for Distribution

Finally, you'll package your app as an MSIX for distribution. This includes:

  • Building your app for production
  • Creating and signing an MSIX package
  • Testing the installed package
  • Understanding distribution options

Package Your App →

Quick Navigation

Phase Guide What You'll Learn
1️⃣ Setup Install tools, initialize SDKs, configure build pipeline
2️⃣ C++ Notification Addon Create C++ addon, call notification APIs, test with debug identity
2️⃣ Phi Silica Addon Create C# addon, call AI APIs, test with debug identity
2️⃣ WinML Addon Create C# addon, call WinML APIs, run ONNX models, integrate ML
3️⃣ Packaging Build production app, create MSIX, distribute

Additional Resources

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