Google Images

🖼️ Google Images API: fast, low-cost bulk image search returning clean JSON

The most efficient, reliable, and developer-friendly way to use the Google Images API.

Actor page: apify.com/johnvc/google-images-api Input schema: apify.com/johnvc/google-images-api/input-schema

Search Google Images in bulk and get back clean, structured JSON for every result: the full-size image URL with its width and height, a thumbnail, the source site and domain, the page the image appears on, and a Google reference URL. Pass many queries at once, localize by country and language, and export thousands of images. You pay per image returned, from $0.10 per 1,000.

Video Walkthrough

Quick Start

Prerequisites

• Python 3.11 or higher
• An Apify account and API key (get a free key here)

1. Clone the repository

   git clone https://github.com/johnisanerd/Google-Images-API.git

cd Google-Images-API

1. Install dependencies with UV

   # Install UV if you do not have it:

curl -LsSf https://astral.sh/uv/install.sh | sh

Install project dependencies:

uv sync

1. Configure your API key

   cp .env.example .env

Edit .env and add your Apify API key

Get your free API key at: https://apify.com?fpr=9n7kx3

1. Run the example

   uv run python google-images-api-example.py

Alternative: set the API key directly

export APIFY_API_TOKEN="your_api_key_here"

uv run python google-images-api-example.py

Why Use This Google Images API?

It is the lowest-cost path to Google Images data. You pay a flat $0.0001 per image, which is $0.10 per 1,000, with no setup fee and no per-run fee. That is roughly 10x below the cheapest mainstream alternative.

It returns clean, predictable JSON. Every result is one row with a stable set of fields, so you can load it straight into a dataframe, a database, or an AI pipeline without reshaping.

It is fast and reliable. The API talks to a structured data service instead of driving a slow, breakable headless browser, so runs finish quickly and consistently.

It is built for batch work. Pass a list of queries and a per-query result count, and the API paginates for you and tags every row with the query it came from.

It is MCP-ready. AI agents can discover and call it as a tool through the hosted Apify MCP server, so an assistant can fetch image results in one step.

Features

Core Capabilities

• Bulk search: pass one or many queries in a single run
• Control the number of images returned per query
• Localize results by country (gl) and language (hl)
• Pagination handled for you, with per-query result tagging

Data Quality

• Full-size imageUrl plus imageWidth and imageHeight
• thumbnailUrl with its own dimensions for fast previews
• source site, domain, and the link to the hosting page
• Stable, flat JSON shape: one row per image, easy to load anywhere

Usage Examples

Basic Example

{

"queries": ["golden retriever puppy"], "maxResultsPerQuery": 10 }

Advanced Example

{

"queries": ["golden retriever puppy", "eiffel tower at night"], "maxResultsPerQuery": 100, "gl": "us", "hl": "en" }

Input Parameters

Output Format

Each item in the dataset is a single image result:

{

"query": "golden retriever puppy", "position": 1, "title": "Golden Retriever Puppy", "imageUrl": "https://images.example.com/products/57215/golden-retriever-puppy.jpg", "imageWidth": 1047, "imageHeight": 699, "thumbnailUrl": "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9Gc...", "thumbnailWidth": 275, "thumbnailHeight": 183, "source": "Photowall", "domain": "www.photowall.com", "link": "https://www.photowall.com/us/golden-retriever-puppy-wallpaper", "googleUrl": "https://www.google.com/imgres?imgurl=..." }

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Install in Claude Cowork Desktop

Cowork is the desktop app's automation mode. To give it the Google Images API as a tool, add the Apify MCP server as a connector.

1. Open the Claude desktop app and go to Settings → Connectors (or Settings → Developer → Edit Config to edit claude_desktop_config.json directly).

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

1. Add the Apify MCP server, preloaded with only this Actor:

{

"mcpServers": { "apify": { "command": "npx", "args": [ "-y", "mcp-remote", "https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api" ] } } }

1. Restart the app. When Cowork first calls the tool, complete the OAuth prompt in your browser, or add your Apify API token in the connector settings to skip OAuth.
2. In a Cowork chat, confirm the tool is available and ask it to run the Google Images API.

Download the desktop app and start a free trial: https://claude.ai/referral/uIlpa7nPLg More help: https://docs.apify.com/platform/integrations/claude-desktop

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Install in Claude Code

Claude Code is the command-line tool. Add the Actor's MCP server with one command:

claude mcp add --transport http apify \

"https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api"

To use a token instead of browser OAuth:

claude mcp add --transport http apify \

"https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api" \ --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the Google Images API.

Try Claude Code free: https://claude.ai/referral/uIlpa7nPLg Claude Code MCP docs: https://code.claude.com/docs/en/mcp

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Install in Claude (website)

On claude.ai you add Apify as a connector, then enable just this Actor's tool.

1. Go to Settings → Connectors → Browse connectors and search for Apify MCP server. Install it (enable or update if prompted).
2. When connecting, authenticate with your Apify API token, and enable the tool johnvc/google-images-api.
3. In any chat, open + → Connectors and turn on Apify.
4. Alternatively, choose Add custom connector and paste the full MCP URL https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api, using OAuth when prompted.
5. Ask Claude to run the Google Images API.

Open Claude on the web: https://claude.ai/referral/uIlpa7nPLg

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Install in Cursor

Cursor reads MCP servers from a project file at .cursor/mcp.json.

1. In your project, create .cursor/mcp.json:

{

"mcpServers": { "apify": { "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api" } } }

1. If you prefer token auth over browser OAuth, add a header:

{

"mcpServers": { "apify": { "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } }

1. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
2. In Composer or Chat, ask Cursor to call the Google Images API.

New to Cursor? Get it here: https://cursor.com/referral?code=XQP4VBLI3NNX

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Install in ChatGPT

ChatGPT connects to the Apify MCP server through Developer mode (available on ChatGPT Pro, Plus, Business, Enterprise, and Education plans).

1. Click your profile icon, then go to Settings > Apps. If you do not see a Create app button, open Advanced settings and enable Developer mode.
2. Click Create app and fill out the form:

• Name: Apify
• MCP Server URL: https://mcp.apify.com/?tools=actors,docs,johnvc/google-images-api
• Authentication: OAuth

1. Click Create and authorize the connection with Apify.
2. To use the app in a conversation, click + in the chat, choose Developer mode, and select Apify.

More help: https://docs.apify.com/platform/integrations/mcp

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Made with care

*Use the Google Images API to power your data workflows with reliable, structured results.*

Featured Tasks

Ready-to-run examples on the Apify Store.

• Export Google Images Results to CSV

🤖 Ask an AI assistant about this Actor

Open a ready-to-send prompt about the Google Images API in the AI of your choice:

• 💬 ChatGPT
• 🧠 Claude
• 🔍 Perplexity
• 🅒 Copilot

Last Updated: 2026.10.27