Azure Static Web Apps logo

Azure Static Web Apps

OrganizationPopular
github
azure-static-web-apps

Helps create, configure, and deploy Azure Static Web Apps using the SWA CLI. Use when deploying static sites to Azure, setting up SWA local development, configuring staticwebapp.config.json, adding Azure Functions APIs to SWA, or setting up GitHub Actions CI/CD for Static Web Apps.

Overview

Publishergithub
Repositoryawesome-copilot
Skill nameazure-static-web-apps
Stars
39.1K
Forks
5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Azure Static Web Apps AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/azure-static-web-apps .claude/skills/azure-static-web-apps
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Static Web Apps in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure Static Web Apps on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure Static Web Apps is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Overview

Azure Static Web Apps (SWA) hosts static frontends with optional serverless API backends. The SWA CLI (swa) provides local development emulation and deployment capabilities.

Key features:

  • Local emulator with API proxy and auth simulation
  • Framework auto-detection and configuration
  • Direct deployment to Azure
  • Database connections support

Config files:

  • swa-cli.config.json - CLI settings, created by swa init (never create manually)
  • staticwebapp.config.json - Runtime config (routes, auth, headers, API runtime) - can be created manually

General Instructions

Installation

bash
npm install -D @azure/static-web-apps-cli

Verify: npx swa --version

Quick Start Workflow

IMPORTANT: Always use swa init to create configuration files. Never manually create swa-cli.config.json.

  1. swa init - Required first step - auto-detects framework and creates swa-cli.config.json
  2. swa start - Run local emulator at http://localhost:4280
  3. swa login - Authenticate with Azure
  4. swa deploy - Deploy to Azure

Configuration Files

swa-cli.config.json - Created by swa init, do not create manually:

  • Run swa init for interactive setup with framework detection
  • Run swa init --yes to accept auto-detected defaults
  • Edit the generated file only to customize settings after initialization

Example of generated config (for reference only):

json
{
  "$schema": "https://aka.ms/azure/static-web-apps-cli/schema",
  "configurations": {
    "app": {
      "appLocation": ".",
      "apiLocation": "api",
      "outputLocation": "dist",
      "appBuildCommand": "npm run build",
      "run": "npm run dev",
      "appDevserverUrl": "http://localhost:3000"
    }
  }
}

staticwebapp.config.json (in app source or output folder) - This file CAN be created manually for runtime configuration:

json
{
  "navigationFallback": {
    "rewrite": "/index.html",
    "exclude": ["/images/*", "/css/*"]
  },
  "routes": [
    { "route": "/api/*", "allowedRoles": ["authenticated"] }
  ],
  "platform": {
    "apiRuntime": "node:20"
  }
}

Command-line Reference

swa login

Authenticate with Azure for deployment.

bash
swa login                              # Interactive login
swa login --subscription-id <id>       # Specific subscription
swa login --clear-credentials          # Clear cached credentials

Flags: --subscription-id, -S | --resource-group, -R | --tenant-id, -T | --client-id, -C | --client-secret, -CS | --app-name, -n

swa init

Configure a new SWA project based on an existing frontend and (optional) API. Detects frameworks automatically.

bash
swa init                    # Interactive setup
swa init --yes              # Accept defaults

swa build

Build frontend and/or API.

bash
swa build                   # Build using config
swa build --auto            # Auto-detect and build
swa build myApp             # Build specific configuration

Flags: --app-location, -a | --api-location, -i | --output-location, -O | --app-build-command, -A | --api-build-command, -I

swa start

Start local development emulator.

bash
swa start                                    # Serve from outputLocation
swa start ./dist                             # Serve specific folder
swa start http://localhost:3000              # Proxy to dev server
swa start ./dist --api-location ./api        # With API folder
swa start http://localhost:3000 --run "npm start"  # Auto-start dev server

Common framework ports:

FrameworkPort
React/Vue/Next.js3000
Angular4200
Vite5173

Key flags:

  • --port, -p - Emulator port (default: 4280)
  • --api-location, -i - API folder path
  • --api-port, -j - API port (default: 7071)
  • --run, -r - Command to start dev server
  • --open, -o - Open browser automatically
  • --ssl, -s - Enable HTTPS

swa deploy

Deploy to Azure Static Web Apps.

bash
swa deploy                              # Deploy using config
swa deploy ./dist                       # Deploy specific folder
swa deploy --env production             # Deploy to production
swa deploy --deployment-token <TOKEN>   # Use deployment token
swa deploy --dry-run                    # Preview without deploying

Get deployment token:

  • Azure Portal: Static Web App → Overview → Manage deployment token
  • CLI: swa deploy --print-token
  • Environment variable: SWA_CLI_DEPLOYMENT_TOKEN

Key flags:

  • --env - Target environment (preview or production)
  • --deployment-token, -d - Deployment token
  • --app-name, -n - Azure SWA resource name

swa db

Initialize database connections.

bash
swa db init --database-type mssql
swa db init --database-type postgresql
swa db init --database-type cosmosdb_nosql

Scenarios

Create SWA from Existing Frontend and Backend

Always run swa init before swa start or swa deploy. Do not manually create swa-cli.config.json.

bash
# 1. Install CLI
npm install -D @azure/static-web-apps-cli

# 2. Initialize - REQUIRED: creates swa-cli.config.json with auto-detected settings
npx swa init              # Interactive mode
# OR
npx swa init --yes        # Accept auto-detected defaults

# 3. Build application (if needed)
npm run build

# 4. Test locally (uses settings from swa-cli.config.json)
npx swa start

# 5. Deploy
npx swa login
npx swa deploy --env production

Add Azure Functions Backend

  1. Create API folder:
bash
mkdir api && cd api
func init --worker-runtime node --model V4
func new --name message --template "HTTP trigger"
  1. Example function (api/src/functions/message.js):
javascript
const { app } = require('@azure/functions');

app.http('message', {
    methods: ['GET', 'POST'],
    authLevel: 'anonymous',
    handler: async (request) => {
        const name = request.query.get('name') || 'World';
        return { jsonBody: { message: `Hello, ${name}!` } };
    }
});
  1. Set API runtime in staticwebapp.config.json:
json
{
  "platform": { "apiRuntime": "node:20" }
}
  1. Update CLI config in swa-cli.config.json:
json
{
  "configurations": {
    "app": { "apiLocation": "api" }
  }
}
  1. Test locally:
bash
npx swa start ./dist --api-location ./api
# Access API at http://localhost:4280/api/message

Supported API runtimes: node:18, node:20, node:22, dotnet:8.0, dotnet-isolated:8.0, python:3.10, python:3.11

Set Up GitHub Actions Deployment

  1. Create SWA resource in Azure Portal or via Azure CLI
  2. Link GitHub repository - workflow auto-generated, or create manually:

.github/workflows/azure-static-web-apps.yml:

yaml
name: Azure Static Web Apps CI/CD

on:
  push:
    branches: [main]
  pull_request:
    types: [opened, synchronize, reopened, closed]
    branches: [main]

jobs:
  build_and_deploy:
    if: github.event_name == 'push' || (github.event_name == 'pull_request' && github.event.action != 'closed')
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Build And Deploy
        uses: Azure/static-web-apps-deploy@v1
        with:
          azure_static_web_apps_api_token: ${{ secrets.AZURE_STATIC_WEB_APPS_API_TOKEN }}
          repo_token: ${{ secrets.GITHUB_TOKEN }}
          action: upload
          app_location: /
          api_location: api
          output_location: dist

  close_pr:
    if: github.event_name == 'pull_request' && github.event.action == 'closed'
    runs-on: ubuntu-latest
    steps:
      - uses: Azure/static-web-apps-deploy@v1
        with:
          azure_static_web_apps_api_token: ${{ secrets.AZURE_STATIC_WEB_APPS_API_TOKEN }}
          action: close
  1. Add secret: Copy deployment token to repository secret AZURE_STATIC_WEB_APPS_API_TOKEN

Workflow settings:

  • app_location - Frontend source path
  • api_location - API source path
  • output_location - Built output folder
  • skip_app_build: true - Skip if pre-built
  • app_build_command - Custom build command

Troubleshooting

IssueSolution
404 on client routesAdd navigationFallback with rewrite: "/index.html" to staticwebapp.config.json
API returns 404Verify api folder structure, ensure platform.apiRuntime is set, check function exports
Build output not foundVerify output_location matches actual build output directory
Auth not working locallyUse /.auth/login/<provider> to access auth emulator UI
CORS errorsAPIs under /api/* are same-origin; external APIs need CORS headers
Deployment token expiredRegenerate in Azure Portal → Static Web App → Manage deployment token
Config not appliedEnsure staticwebapp.config.json is in app_location or output_location
Local API timeoutDefault is 45 seconds; optimize function or check for blocking calls

Debug commands:

bash
swa start --verbose log        # Verbose output
swa deploy --dry-run           # Preview deployment
swa --print-config             # Show resolved configuration

Frequently asked questions

What does the Azure Static Web Apps AI skill do?

Helps create, configure, and deploy Azure Static Web Apps using the SWA CLI. Use when deploying static sites to Azure, setting up SWA local development, configuring staticwebapp.config.json, adding Azure Functions APIs to SWA, or setting up GitHub Actions CI/CD for Static Web Apps.

Why use Azure Static Web Apps on TypingMind?

Because you install it once and use it with any model. Azure Static Web Apps is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure Static Web Apps in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/azure-static-web-apps. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Azure Static Web Apps?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure Static Web Apps?

As many as you like. As long as a model supports skills, you can use Azure Static Web Apps with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure Static Web Apps AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇