# ✨ Google Images Scraper (`damilo/google-images-scraper`) Actor ⚡️ Blazing-fast Google Images Scraper. Fetch image URLs, alt-text & titles by keyword in seconds. Delivers clean JSON for AI training, visual research, and automated content pipelines. - **URL**: https://apify.com/damilo/google-images-scraper.md - **Developed by:** [Imad](https://apify.com/damilo) (community) - **Categories:** AI, Automation, SEO tools - **Stats:** 403 total users, 59 monthly users, 99.9% runs succeeded, 10 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Google Images Scraper ✅ If this actor saved you time, a ⭐⭐⭐⭐⭐ review helps me keep improving! Need to scrape Google Images fast and reliably? This **Google Images Scraper** is the perfect tool to extract image search results by keyword — optimized for speed, clean output, and SEO accuracy. Whether you're training AI models, building content workflows, or doing research, this scraper gets you structured image data in seconds. --- ### Table of Contents 1. [Features](#features) 2. [Input Parameters](#input-parameters) 3. [Example Input](#example-input) 4. [Output](#output) 5. [Use Cases](#use-cases) 6. [Support](#support) --- ### Features - ⚡ **Blazing Fast**: Scrapes Google Images in seconds. - 🔍 **Keyword Search**: Input any keyword and get relevant images. - 🌍 **Localized Results**: Supports country and language targeting. - 📦 **Structured Output**: Clean JSON with all key image metadata. - 🧠 **SEO-Ready**: Ideal for AI training, content enrichment, and image sourcing. --- ### Input Parameters | Key | Type | Required | Default | Description | | ------------ | ------- | -------- | --------- | ---------------------------------------------------------------- | | `query` | string | Yes | – | The search query you want to scrape from Google Images. | | `country` | string | No | `us` | Country code to localize results (e.g., `us`, `gb`, `fr`, etc.). | | `language` | string | No | `en` | Language of the search interface. | | `num` | integer | No | `10` | Number of results per page. | | `max_pages` | integer | Yes | `1` | Number of pages to scrape. | | `date_range` | string | No | `anytime` | Filter images by upload date. | --- ### Example Input ```json { "query": "futuristic city art", "country": "us", "language": "en", "num": "20", "max_pages": 2, "date_range": "anytime" } ```` *** ### Output The scraper returns an array of image search results with the following structure: ```json [ { "title": "Futuristic City Wallpaper", "imageUrl": "https://images.example.com/image.jpg", "thumbnailUrl": "https://images.example.com/thumb.jpg", "link": "https://source-website.com/page.html", "googleUrl": "https://www.google.com/imgres?..." }, ... ] ``` *** ### Use Cases - 🔎 AI/ML model training with real-world image data - 🧩 Content automation and media enrichment - 📊 Trend analysis for visual search - 📰 Editorial or design inspiration sourcing - 🎨 Art and concept dataset creation - ... *** ### Support Have questions or feature requests? - Visit the Apify community forums. - Submit an issue directly on the Apify platform. *** ### Why Use This Google Images Scraper? This scraper is optimized for developers, marketers, researchers, and creators who need quick, clean access to Google Images. It's lightweight, powerful, and fully customizable to your search needs — with blazing-fast performance you can rely on. *** Happy scraping! # Actor input Schema ## `query` (type: `string`): The query to search for. ## `country` (type: `string`): The country to search in. ## `language` (type: `string`): The language to search in. ## `num` (type: `string`): Number of results per page to scrape. ## `max_pages` (type: `integer`): The maximum number of pages to scrape. ## `date_range` (type: `string`): The date range to search for. ## Actor input object example ```json { "query": "dogs", "country": "us", "language": "en", "num": "10", "max_pages": 1, "date_range": "anytime" } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "query": "dogs", "country": "us", "language": "en", "num": "10", "max_pages": 1, "date_range": "anytime" }; // Run the Actor and wait for it to finish const run = await client.actor("damilo/google-images-scraper").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": "dogs", "country": "us", "language": "en", "num": "10", "max_pages": 1, "date_range": "anytime", } # Run the Actor and wait for it to finish run = client.actor("damilo/google-images-scraper").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 '{ "query": "dogs", "country": "us", "language": "en", "num": "10", "max_pages": 1, "date_range": "anytime" }' | apify call damilo/google-images-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=damilo/google-images-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "✨ Google Images Scraper", "description": "⚡️ Blazing-fast Google Images Scraper. Fetch image URLs, alt-text & titles by keyword in seconds. Delivers clean JSON for AI training, visual research, and automated content pipelines.", "version": "0.0", "x-build-id": "tsq4CG5JIukvmbYj4" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/damilo~google-images-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-damilo-google-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/damilo~google-images-scraper/runs": { "post": { "operationId": "runs-sync-damilo-google-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/damilo~google-images-scraper/run-sync": { "post": { "operationId": "run-sync-damilo-google-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "query", "num", "country", "date_range", "language" ], "properties": { "query": { "title": "Search query", "type": "string", "description": "The query to search for.", "default": "dogs" }, "country": { "title": "Country", "enum": [ "af", "al", "dz", "as", "ad", "ao", "ai", "aq", "ag", "ar", "am", "aw", "au", "at", "az", "bs", "bh", "bd", "bb", "by", "be", "bz", "bj", "bm", "bt", "bo", "ba", "bw", "bv", "br", "io", "bn", "bg", "bf", "bi", "kh", "cm", "ca", "cv", "ky", "cf", "td", "cl", "cn", "cx", "cc", "co", "km", "cg", "cd", "ck", "cr", "ci", "hr", "cu", "cy", "cz", "dk", "dj", "dm", "do", "ec", "eg", "sv", "gq", "er", "ee", "et", "fk", "fo", "fj", "fi", "fr", "gf", "pf", "tf", "ga", "gm", "ge", "de", "gh", "gi", "gr", "gl", "gd", "gp", "gu", "gt", "gn", "gw", "gy", "ht", "hm", "va", "hn", "hk", "hu", "is", "in", "id", "ir", "iq", "ie", "il", "it", "jm", "jp", "jo", "kz", "ke", "ki", "kp", "kr", "kw", "kg", "la", "lv", "lb", "ls", "lr", "ly", "li", "lt", "lu", "mo", "mk", "mg", "mw", "my", "mv", "ml", "mt", "mh", "mq", "mr", "mu", "yt", "mx", "fm", "md", "mc", "mn", "ms", "ma", "mz", "mm", "na", "nr", "np", "nl", "an", "nc", "nz", "ni", "ne", "ng", "nu", "nf", "mp", "no", "om", "pk", "pw", "ps", "pa", "pg", "py", "pe", "ph", "pn", "pl", "pt", "pr", "qa", "re", "ro", "ru", "rw", "sh", "kn", "lc", "pm", "vc", "ws", "sm", "st", "sa", "sn", "rs", "sc", "sl", "sg", "sk", "si", "sb", "so", "za", "gs", "es", "lk", "sd", "sr", "sj", "sz", "se", "ch", "sy", "tw", "tj", "tz", "th", "tl", "tg", "tk", "to", "tt", "tn", "tr", "tm", "tc", "tv", "ug", "ua", "ae", "gb", "us", "um", "uy", "uz", "vu", "ve", "vn", "vg", "vi", "wf", "eh", "ye", "zm", "zw" ], "type": "string", "description": "The country to search in.", "default": "us" }, "language": { "title": "Language", "enum": [ "af", "ak", "sq", "am", "ar", "hy", "az", "eu", "be", "bem", "bn", "bh", "xx-bork", "bs", "br", "bg", "km", "ca", "chr", "ny", "zh-cn", "zh-tw", "co", "hr", "cs", "da", "nl", "xx-elmer", "en", "eo", "et", "ee", "fo", "tl", "fi", "fr", "fy", "gaa", "gl", "ka", "de", "el", "gn", "gu", "xx-hacker", "ht", "ha", "haw", "iw", "hi", "hu", "is", "ig", "id", "ia", "ga", "it", "ja", "jw", "kn", "kk", "rw", "rn", "xx-klingon", "kg", "ko", "kri", "ku", "ckb", "ky", "lo", "la", "lv", "ln", "lt", "loz", "lg", "ach", "mk", "mg", "ms", "ml", "mt", "mi", "mr", "mfe", "mo", "mn", "sr-ME", "ne", "pcm", "nso", "no", "nn", "oc", "or", "om", "ps", "fa", "xx-pirate", "pl", "pt", "pt-br", "pt-pt", "pa", "qu", "ro", "rm", "nyn", "ru", "gd", "sr", "sh", "st", "tn", "crs", "sn", "sd", "si", "sk", "sl", "so", "es", "es-419", "su", "sw", "sv", "tg", "ta", "tt", "te", "th", "ti", "to", "lua", "tum", "tr", "tk", "tw", "ug", "uk", "ur", "uz", "vi", "cy", "wo", "xh", "yi", "yo", "zu" ], "type": "string", "description": "The language to search in.", "default": "en" }, "num": { "title": "Number of results per page to scrape", "enum": [ "10", "100" ], "type": "string", "description": "Number of results per page to scrape.", "default": "10" }, "max_pages": { "title": "Max pages to scrape", "type": "integer", "description": "The maximum number of pages to scrape.", "default": 1 }, "date_range": { "title": "Date range", "enum": [ "anytime", "qdr:h", "qdr:d", "qdr:w", "qdr:m" ], "type": "string", "description": "The date range to search for.", "default": "anytime" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```