skapi-js
v1.5.0-beta.9
Published
Serverless Backend API for AI Agents.
Maintainers
broadwayincReadme
Skapi
Tested environments: Node 18/20/22, CommonJS, ESM, TypeScript consumers, Browser UMD bundle.
Zero-Setup Serverless Backend
Skapi is a backend API that runs entirely serverless—no complex installations, no server configurations, and no database management required. Build full-featured web applications faster and focus on what matters: your product.
Works Everywhere: Vanilla HTML, SPAs, and AI Agents
No fancy frameworks or complex deployments needed. Skapi is a single JavaScript library that works seamlessly with vanilla HTML, modern frameworks like React, Vue, and Angular, and integrates effortlessly with AI-powered development tools.
All-in-One Package
Skapi provides all the backend features you need for your web application out of the box, without the need to set up or maintain any backend servers.
- Authentication
- Database
- File Storage
- Realtime websocket messaging
- WebRTC media streaming
- Notification
- CDN
- Automated Email Systems
- API Bridge for 3rd party APIs
- File Hosting
Getting Started
1. Create a service
- Signup for an account at skapi.com.
- Log in and create a new service from the
My Servicespage.
2. Initialize the Skapi library
Skapi is compatible with both vanilla HTML and webpack-based projects (ex. Vue, React, Angular... etc).
You need to import the library using the <script> tag or install via npm.
For HTML projects:
For vanilla HTML projects, import Skapi in the script tag, and initialize the library.
<!DOCTYPE html>
<script src="https://cdn.jsdelivr.net/npm/skapi-js@latest/dist/skapi.js"></script>
<script>
const skapi = new Skapi('SERVICE_ID');
</script>Be sure to replace 'SERVICE_ID' with the actual ID of your service
For more information, check out our documentation.
For SPA projects:
To use Skapi in a SPA projects (such as Vue, React, or Angular), you can install skapi-js via npm.
$ npm i skapi-jsThen, import the library into your main JavaScript file.
// main.js
import { Skapi } from 'skapi-js';
const skapi = new Skapi('SERVICE_ID');
// Export the skapi instance, so you can use it in other component files
export { skapi }TypeScript (React, Vue, etc.)
import { Skapi } from 'skapi-js';
import type { RecordData, DatabaseResponse } from 'skapi-js';
const skapi = new Skapi('SERVICE_ID');
let databaseRecords: DatabaseResponse<RecordData>;Node.js (CommonJS)
To use Skapi in NodeJS, import the library as shown below:
const { Skapi } = require('skapi-js');
const skapi = new Skapi('SERVICE_ID');Node.js (ESM)
import { Skapi } from 'skapi-js';
const skapi = new Skapi('SERVICE_ID');Note: When running Skapi in Node.js, browser-specific features such as WebSocket, WebRTC, and Notifications are not available.
3. Test your connection
After you initialized the Skapi library, you can test your connection by pinging your request with the mock() method.
Below is an example of how you can use the mock() method in HTML forms.
<!-- index.html -->
<!DOCTYPE html>
<script src="https://cdn.jsdelivr.net/npm/skapi-js@latest/dist/skapi.js"></script>
<script>
const skapi = new Skapi('SERVICE_ID');
</script>
<form onsubmit='skapi.mock(event).then(ping=>alert(ping.msg))'>
<input name='msg' placeholder='Test message'>
<input type='submit' value='Test Connection'>
</form>This will send a request to your Skapi service and ping back the response.
When the request is resolved, the mock() method will return the response data as a Promise object.
The response data will be displayed in an alert box.
AI-Driven Development
Skapi works seamlessly with AI-powered coding assistants.
To help your assistant understand how to integrate the Skapi API into your project, download and use the system prompt file described below.
For Chat-Based Platforms (e.g., ChatGPT, Lovable)
1. Download the system prompt file
⬇️ SKAPI.md (Click to Download)
2. Go to your AI website and send a prompt
In your AI chat website or app (for example, ChatGPT at chat.openai.com or Lovable), start a new chat, attach the SKAPI.md file, and paste the following as your first LLM prompt:
Use the file "SKAPI.md" as a system prompt.
My Skapi service ID is: "xxxxxxxxxxxx-xxxxx-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx".
Build me a [describe what you want].Replace the placeholder service ID with your actual service ID, and customize the last line with what you want to build.
For AI Code Generators (e.g., Claude Code, OpenAI Codex, Gemini CLI)
1. Download the system prompt file
⬇️ SKAPI.md (Click to Download)
2. Rename and add it to your project
Rename the downloaded SKAPI.md file to a filename your tool recognizes, then add it to your project folder.
Examples:
- AGENT.md for OpenAI Codex
- CLAUDE.md for Anthropic Claude
- GEMINI.md for Gemini CLI
3. Start writing prompts
When you invoke your code generator, include a prompt like:
My Skapi service ID is: "xxxxxxxxxxxx-xxxxx-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx".
Build me a [describe what you want].Replace the placeholder service ID with your actual service ID before you run the command.