# Web Image Optimization Batch — WebP/AVIF Size Savings (`snapperwapper/image-converter-batch`) Actor

Convert bounded public image batches to WebP, AVIF, JPEG, or PNG with resizing, byte savings evidence, and stored artifacts.

- **URL**: https://apify.com/snapperwapper/image-converter-batch.md
- **Developed by:** [snapperwapper](https://apify.com/snapperwapper) (community)
- **Categories:** Developer tools, Automation, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Web Image Optimization Batch — WebP/AVIF Size Savings

Convert and resize up to 25 authorized public images to WebP, AVIF, JPEG, or PNG for CMS pipelines and automation-ready web delivery.

### Input

```json
{"urls":["https://www.w3.org/Icons/w3c_home.png"],"format":"webp","quality":80,"width":600,"fit":"inside"}
```

### Output

Each Dataset row reports source/output format, dimensions, byte counts, status, and an `IMAGE_*` key for the converted binary in the run key-value store. Invalid items produce error rows without stopping valid siblings.

### Limits and safety

- 25 URLs/run; 20 MB input/image; 8 MiB output/image
- SVG is rejected; decoded and output images are capped at 4,096 px/axis and 16.8 MP
- redirects are manual and bounded; socket-time DNS validation blocks non-public destinations
- metadata is stripped by default

Process only images you are authorized to transform.

# Actor input Schema

## `urls` (type: `array`):

One to 25 public image URLs, up to 20 MB each.

## `format` (type: `string`):

Target image encoding format.

## `quality` (type: `integer`):

Lossy output quality from 20 to 100.

## `width` (type: `integer`):

Optional output width in pixels.

## `height` (type: `integer`):

Optional output height in pixels.

## `fit` (type: `string`):

How the image fits the requested width and height.

## `stripMetadata` (type: `boolean`):

Remove embedded metadata from converted images by default.

## Actor input object example

```json
{
  "urls": [
    "https://www.w3.org/Icons/w3c_home.png"
  ],
  "format": "webp",
  "quality": 80,
  "fit": "inside",
  "stripMetadata": true
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("snapperwapper/image-converter-batch").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("snapperwapper/image-converter-batch").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call snapperwapper/image-converter-batch --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=snapperwapper/image-converter-batch",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/mDNxkiT9RyuU26qTq/builds/KmuBs0kjX0w2gKD7w/openapi.json