# Bing Images Scraper API (`thodor/bing-images`) Actor Scrape Bing image search results in bulk. Drop-in alternative to the discontinued Microsoft Bing Image Search API. No API key required. - **URL**: https://apify.com/thodor/bing-images.md - **Developed by:** [Thodor](https://apify.com/thodor) (community) - **Categories:** Other, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.20 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Bing Images Scraper API Scrape Bing image search results in bulk. Pass one or more keywords, get hundreds of unique full-size image URLs back per query, with source pages, titles, and metadata. A drop-in **Bing Image Search API alternative**. No Microsoft Azure subscription, no Bing API key, no quota negotiations. ### Why use this Bing images scraper Microsoft [retired the Bing Search APIs](https://learn.microsoft.com/en-us/bing/search-apis/bing-image-search/overview) (including the Bing Image Search API v7) in August 2025 and replaced them with the much more expensive ["Grounding with Bing Search"](https://learn.microsoft.com/en-us/azure/ai-services/agents/how-to/tools/bing-grounding) inside Azure AI Foundry, with rate limits, mandatory Azure billing, and content restrictions. Most teams that used the Bing Image Search API have been left without a working replacement. This actor fills that gap. Send a keyword, get structured JSON back with full-size image URLs and source pages, the same shape a Bing Images API would have returned. No Microsoft API key, no Azure billing setup. Coverage is also deeper than the old API ever offered: we hit Bing across multiple markets and proxy regions to pull hundreds of unique results per query, instead of the 35 you would see in a browser. **Common use cases:** - Bulk download Bing images for ML training datasets, face datasets, product datasets, etc. - E-commerce product image research and competitor monitoring - SEO and brand monitoring across Bing regions - Stock photo, reference, and content collection - Replacement for legacy code that called `api.bing.microsoft.com/v7.0/images/search` ### Bing Image Search API alternative If you used to call the official Microsoft Bing Image Search API, this actor gives you the same thing without the Microsoft side of the equation: - **No Microsoft API key, no Azure subscription, no quota requests.** Just an Apify account. - **One row per unique image.** Each result carries Bing's md5 hash so you can de-dup further across queries yourself. - **Hundreds of unique results per query.** Queries Bing across multiple markets and residential-proxy egress regions to surface long-tail images you cannot get from a single browser view. - **JSON output** out of the box, with one-click **CSV export**, Excel, XML, and HTML from the Apify console. - **You own the output.** Unlike Microsoft's [Grounding with Bing Search](https://learn.microsoft.com/en-us/azure/ai-services/agents/how-to/tools/bing-grounding), there are no content-storage restrictions: keep the results, cache them, train on them. ### Features - **Full-size image URLs.** The actual image file from the source website, not a Bing thumbnail. - **Bing image metadata.** Title, source page, image hash (md5), thumbnail URL, image ID. - **Bulk download Bing images.** Hundreds of unique results per query, multi-query batching in one actor run. - **Multi-region coverage.** Queries Bing across European, US, and Asian markets (toggleable) plus residential proxy egress from multiple continents, so you get more unique images than a single browser session can see. - **Per-result provenance.** Every row tells you which market and which proxy country surfaced it. Useful for debugging surprising results: searching "cat" returns *very* different images from Bing Japan vs Bing Europe. - **No code required.** Fill in a couple of fields in the [Apify console](https://console.apify.com/) and run, nothing to install. - **JSON, CSV, Excel, XML output.** Exported from the console or via the [Apify Dataset API](https://docs.apify.com/platform/storage/dataset). - **Resilient.** Built on [Apify residential proxies](https://docs.apify.com/platform/proxy/residential-proxy) with country-level fallback so a single bad IP doesn't kill the run. ### How to scrape Bing Images 1. Enter one or more keywords in the **Search queries** field (one keyword per line) 2. Toggle which regions to scan: **Europe** (default on), **US** (default on), **Asia** (default off; enable for Asian subjects) 3. Optionally set **Single market override** if you want a specific Bing market like `pt-BR` or `ar-SA` 4. Run the actor. It typically takes 10–20 seconds per query 5. Export results from the dataset as JSON or CSV That's it. No Azure, no Microsoft API key, no quota forms. ### Input | Parameter | Type | Default | Description | |---|---|---|---| | `queries` | string[] | required | One or more Bing image search keywords | | `scanEU` | boolean | `true` | Query Bing's European markets (nl-BE, en-GB) | | `scanUS` | boolean | `true` | Query Bing's US market (en-US) | | `scanAsia` | boolean | `false` | Query Bing's Asian markets (ja-JP), opt-in | | `marketOverride` | string | `null` | Single Bing `mkt` code (e.g. `pt-BR`). Overrides region toggles. | | `safeSearch` | boolean | `false` | Bing's adult-content filter. Off by default for max coverage; set `true` if you want Bing's default moderate filter. | #### Example input ```json { "queries": ["red running shoes", "blue running shoes"], "scanEU": true, "scanUS": true, "scanAsia": false, "pages": 3 } ```` ### Output Each row in the dataset is one unique image. **Dedup is per-query.** If the same image appears under two of your queries, you get two rows (one per query), so billing matches exactly what you asked for. The `md5` field is included so you can dedup across queries yourself if you want. #### Output fields | Field | Description | |---|---| | `query` | The search term that returned this image | | `image_url` | The full-size image URL on the source site | | `page_url` | The webpage that hosts the image | | `thumbnail_url` | Bing's CDN thumbnail (fast to display) | | `title` | The image title / source page title | | `md5` | Bing's image hash (use this to dedup across queries) | | `mid` | Bing's internal image ID | | `cid` | Bing's content ID | | `desc` | Image description (when Bing provides one) | | `regions` | Which world regions surfaced this image (`["EU", "US"]`, etc.) | | `markets` | Which Bing `mkt` codes returned this image | | `proxy_countries` | Which proxy egress countries this image came back from | | `provenance` | Full list of `(market, region, proxy_country)` tuples for debugging | #### Example output ```json { "query": "bart de wever", "image_url": "https://upload.wikimedia.org/.../Bart_De_Wever_2025.jpg", "page_url": "https://nl.wikipedia.org/wiki/Bart_De_Wever", "thumbnail_url": "https://ts4.mm.bing.net/th?id=OIP...", "title": "Bart De Wever — Wikipedia", "md5": "138a8fac7b9e922fb529b9ce1ef932ae", "mid": "C362FFB13282E2BA48442A27A87AC2006C798887", "cid": "E4qPrHue", "desc": "Belgian Prime Minister", "regions": ["EU", "US"], "markets": ["nl-BE", "en-GB", "en-US"], "proxy_countries": ["DE", "AE"], "provenance": [ {"market": "nl-BE", "region": "EU", "proxy_country": "DE"}, {"market": "en-GB", "region": "EU", "proxy_country": "DE"}, {"market": "en-US", "region": "US", "proxy_country": "AE"} ] } ``` ### Use with Python Call the actor from Python using the Apify client: ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("thodor/bing-images").call(run_input={ "queries": ["red running shoes"], "scanEU": True, "scanUS": True, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["image_url"]) ``` ### Use with Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('thodor/bing-images').call({ queries: ['red running shoes'], scanEU: true, scanUS: true, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach(item => console.log(item.image_url)); ``` You can also call the actor via plain HTTP, run it from the Apify Console with no code at all, or trigger it from Zapier, Make, n8n, and other integrations. ### FAQ #### Is the Bing Image Search API still available? No. Microsoft retired the Bing Search APIs in August 2025. The official replacement, "Grounding with Bing Search" inside Azure AI Foundry, requires an Azure subscription and restricts how you can store and reuse results. This actor is a working alternative with no Microsoft API key and no Azure billing setup. #### Do I need a Microsoft or Azure account? No. You only need a free Apify account. Apify has a [**free plan**](https://apify.com/pricing) with monthly credits, so small jobs run at no cost. #### Is there a free Bing Image Search API? The official Microsoft Bing Image Search API never had a real free tier, and it was retired in August 2025. This actor is the closest thing in 2026: every new Apify account comes with **free starting credit** (no credit card required), enough to test the actor on a batch of queries before deciding whether to subscribe. Current pricing is shown on the Apify actor page above. #### Does this support Bing Visual Search / reverse image search? Not yet. This actor handles **keyword search** (the old `images/search` endpoint). For reverse image search (finding where an image appears online), Google Lens has the deepest index. See my [Google Lens reverse image search actor](https://apify.com/thodor/google-lens-exact-matches) for that use case. If a Bing reverse image search API is something you need, message me and I'll prioritize it. #### How many results do I get per query? Typically 200–350 unique images per query with the default settings (Europe + US scan). Enable the Asia toggle to add ~50 more. The exact number depends on how much content Bing has indexed for your keyword. Niche topics return less, broad topics return more. #### Why are there sometimes duplicate-looking images across markets? Bing serves different rankings of overlapping images across its regional indexes. The actor dedups by Bing's `md5` hash within each query, so what looks like a duplicate in the output is genuinely a different image file (cropped differently, resized differently, or hosted on a different site). If you want to dedup further yourself, group by `md5`. #### Can I export to CSV or Excel? Yes. The [Apify dataset](https://docs.apify.com/platform/storage/dataset) exports to JSON, CSV, Excel, XML, RSS, and HTML directly from the Apify console, or through the Dataset API. No code required. #### Can I extract Bing image URLs at scale? Yes. This is exactly what the actor is built for. Submit a list of keywords in `queries` and it returns hundreds of unique full-size image URLs per keyword. Useful for bulk image dataset building, web scraping pipelines, ML training, e-commerce, and SEO research. #### How does this compare to using the Bing website directly? A normal browser session against Bing Images returns 35–47 results on the first page and another ~25–35 per scroll. This actor queries Bing across multiple markets and proxy regions in parallel, so you get hundreds of unique images per query in 10–20 seconds, versus dozens of manual scrolls and copy-paste from a browser. #### Will Bing block me? Not under normal use. This Bing images scraper uses [Apify residential proxies](https://docs.apify.com/platform/proxy/residential-proxy) and TLS-impersonated requests to look like a real browser. Bing is much more permissive than Google here. We have not seen rate limits or captchas across thousands of test queries. ### Limitations - **Bing Visual Search (reverse image search) is not yet supported.** Only keyword search. Reach out if you need this. - Result counts depend on Bing's index for your keyword. Very obscure terms may return only a handful of images. - Apify residential proxies are required (default and recommended). Datacenter proxies will likely get a degraded response from Bing. ### See also Other image-scraping actors I maintain: - [**Google Images Scraper**](https://apify.com/thodor/google-images-up-to-30k): bulk scrape Google image search results, up to 30,000 unique full-size images per keyword. - [**Google Lens Reverse Image Search**](https://apify.com/thodor/google-lens-exact-matches): find where an image appears online via Google Lens (the reverse-image-search counterpart to this scraper). ### Support Something not working, or missing a feature you need (Bing Visual Search, a specific region, structured filters)? Message me in the Issues tab and I'll look into it. — Thodor P.S. If it works well for you, please leave a review! # Actor input Schema ## `queries` (type: `array`): One or more Bing image search terms (one per line). Each runs independently; you get ~200–350 unique full-size image URLs per query. ## `scanEU` (type: `boolean`): Include Bing's European markets. Recommended for any Western subject. ## `scanUS` (type: `boolean`): Include Bing's US market. Recommended for any non-niche subject. ## `scanAsia` (type: `boolean`): Include Bing's Asian markets. Enable for subjects with Asian presence (J-pop, anime, Asian sports, etc.). Adds ~25% to the result count. ## `marketOverride` (type: `string`): OPTIONAL. A single Bing market code (e.g. pt-BR, ar-SA, ko-KR). If set, the region toggles above are ignored and only this market is queried. Use this for niche/non-Western coverage. ## `safeSearch` (type: `boolean`): Turn Bing's adult-content filter on. Default is OFF (more coverage; recommended for ML training datasets and bulk image collection). Enable if you want Bing's default moderate filtering. ## Actor input object example ```json { "queries": [ "bart de wever" ], "scanEU": true, "scanUS": true, "scanAsia": false, "safeSearch": false } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "queries": [ "bart de wever" ] }; // Run the Actor and wait for it to finish const run = await client.actor("thodor/bing-images").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 = { "queries": ["bart de wever"] } # Run the Actor and wait for it to finish run = client.actor("thodor/bing-images").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 '{ "queries": [ "bart de wever" ] }' | apify call thodor/bing-images --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thodor/bing-images", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bing Images Scraper API", "description": "Scrape Bing image search results in bulk. Drop-in alternative to the discontinued Microsoft Bing Image Search API. No API key required.", "version": "0.2", "x-build-id": "lhyt9ncZNLzSnCkNn" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thodor~bing-images/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thodor-bing-images", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/thodor~bing-images/runs": { "post": { "operationId": "runs-sync-thodor-bing-images", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/thodor~bing-images/run-sync": { "post": { "operationId": "run-sync-thodor-bing-images", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "queries": { "title": "Search queries", "minItems": 1, "uniqueItems": true, "type": "array", "description": "One or more Bing image search terms (one per line). Each runs independently; you get ~200–350 unique full-size image URLs per query.", "items": { "type": "string" } }, "scanEU": { "title": "Scan Europe", "type": "boolean", "description": "Include Bing's European markets. Recommended for any Western subject.", "default": true }, "scanUS": { "title": "Scan US", "type": "boolean", "description": "Include Bing's US market. Recommended for any non-niche subject.", "default": true }, "scanAsia": { "title": "Scan Asia", "type": "boolean", "description": "Include Bing's Asian markets. Enable for subjects with Asian presence (J-pop, anime, Asian sports, etc.). Adds ~25% to the result count.", "default": false }, "marketOverride": { "title": "Single market override", "type": "string", "description": "OPTIONAL. A single Bing market code (e.g. pt-BR, ar-SA, ko-KR). If set, the region toggles above are ignored and only this market is queried. Use this for niche/non-Western coverage." }, "safeSearch": { "title": "SafeSearch", "type": "boolean", "description": "Turn Bing's adult-content filter on. Default is OFF (more coverage; recommended for ML training datasets and bulk image collection). Enable if you want Bing's default moderate filtering.", "default": false } } }, "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 } } } } } } } } } } ```