# Bing Search Scraper - Low-costπŸ’²πŸ”₯πŸŒπŸ” (`delectable_incubator/bing-search-scraper---low-cost`) Actor Scrape Bing search results easily πŸ”πŸŒ with a powerful SERP scraper. Extract titles, URLs, snippets, rankings, domains, thumbnails, and dates for any keyword. Ideal for SEO research, competitor analysis, content discovery, trend tracking, and structured SERP datasets at scale πŸ“ŠπŸš€ - **URL**: https://apify.com/delectable\_incubator/bing-search-scraper---low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** SEO tools, Lead generation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Search Scraper

--- ### Bing Search Scraper πŸŒπŸ“ŠπŸ”Ž The Bing Search Scraper is a fast and scalable Apify Actor designed to extract structured search engine results directly from Bing. It helps you perform SEO research, monitor competitors, analyze trends, discover content opportunities, and build structured SERP datasets across multiple keywords. --- ### 🎯 What This Scraper Does Simply provide one or more keywords and the scraper handles everything automatically. βœ… Performs Bing search queries βœ… Supports multiple keywords in one run βœ… Applies optional time-based filters βœ… Extracts structured organic search results βœ… Stops at your defined limit per keyword βœ… Ideal for SEO, research & lead generation βœ… Ready for automation workflows --- ### πŸ“Š Data Extracted πŸ”Ž Search Result Information | Field | Description | | -------------------- | ------------------------------ | | πŸ”‘ `keyword` | Search keyword used | | πŸ”’ `position` | Ranking position in Bing | | 🏷️ `title` | Result title | | πŸ”— `url` | Direct result link | | 🌐 `displayedUrl` | Visible URL shown in SERP | | πŸ“ `snippet` | Meta description / snippet | | 🌍 `domain` | Root domain | | πŸ–ΌοΈ `thumbnail` | Thumbnail image (if available) | | πŸ“… `date` | Published date (if available) | | ⏱️ `searchTimestamp` | Date & time of the search | --- ### πŸ›  How to Use 1️⃣ Configure Input Provide keywords and settings: ```` { "keywords": \[ "Artificial Intelligence trends", "SEO strategies 2026" ], "TIME\_FILTER": "week", "MAX\_ITEMS\_PER\_KEYWORD": 50 } ``` 2️⃣ Run the Actor β€’ Performs Bing search for each keyword β€’ Applies time filter if selected β€’ Extracts structured SERP results β€’ Automatically moves to next keyword β€’ Stops when limit is reached 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "keywords": \["machine learning", "digital marketing"], "TIME\_FILTER": "month", "MAX\_ITEMS\_PER\_KEYWORD": 100 } ``` #### Input Fields | Field | Type | Description | | ----------------------- | ------ | ---------------------------------------- | | `keywords` | array | List of search keywords (bulk supported) | | `TIME_FILTER` | string | Filter results by recency | | `MAX_ITEMS_PER_KEYWORD` | number | Max results per keyword | --- ### πŸ“€ Output Example ``` { "keyword": "Artificial Intelligence trends", "position": 1, "title": "Top AI Trends to Watch in 2026", "url": "https://example.com/ai-trends", "displayedUrl": "example.com/ai-trends", "snippet": "Discover the latest AI trends shaping the future...", "domain": "example.com", "thumbnail": "https://example.com/image.jpg", "date": "Feb 2026", "searchTimestamp": "2026-02-12T14:32:21.000Z" } ```` --- ### πŸ“Š Output explanation | Use Case | Description | | ---------------------------- | ---------------------------------------- | | πŸ“ˆ SEO Research | Analyze rankings and SERP structure | | πŸ•΅οΈ Competitor Monitoring | Track competitors across keywords | | πŸ“° Trend Tracking | Discover emerging topics | | πŸ’‘ Content Ideation | Find content opportunities | | πŸ“Š Data & Analytics Projects | Build structured datasets for insights | | πŸ” Lead Generation | Identify relevant websites and prospects | --- ### 🌍 Why Use This Scraper? πŸš€ Extract Bing search data at scale πŸ“Š Build structured SEO datasets ⚑ Fast and automated scraping πŸ” Rich metadata for each result πŸ“ˆ Perfect for SEO, research & analytics --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with or endorsed by Bing. --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $2.98 / 1000 results --- ### Related Actors If you're interested in other Bing scraping solutions, explore more tools: (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation Contact for custom scraping solutions or enterprise requests via Apify or by email. # Actor input Schema ## `keywords` (type: `array`): List of keywords or subjects to search for. Each keyword will be scraped separately. ## `TIME_FILTER` (type: `string`): Filter results by date ## `MAX_ITEMS_PER_KEYWORD` (type: `integer`): Maximum number of results to extract per keyword ## Actor input object example ```json { "keywords": [ "Web", "Nature" ], "TIME_FILTER": "any", "MAX_ITEMS_PER_KEYWORD": 30 } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "Web", "Nature" ], "TIME_FILTER": "any", "MAX_ITEMS_PER_KEYWORD": 30 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/bing-search-scraper---low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keywords": [ "Web", "Nature", ], "TIME_FILTER": "any", "MAX_ITEMS_PER_KEYWORD": 30, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/bing-search-scraper---low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "Web", "Nature" ], "TIME_FILTER": "any", "MAX_ITEMS_PER_KEYWORD": 30 }' | apify call delectable_incubator/bing-search-scraper---low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/bing-search-scraper---low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bing Search Scraper - Low-costπŸ’²πŸ”₯πŸŒπŸ”", "description": "Scrape Bing search results easily πŸ”πŸŒ with a powerful SERP scraper. \n\nExtract titles, URLs, snippets, rankings, domains, thumbnails, and dates for any keyword. \n\nIdeal for SEO research, competitor analysis, content discovery, trend tracking, and structured SERP datasets at scale πŸ“ŠπŸš€", "version": "0.0", "x-build-id": "auNHfQ9d5qR5dS0NE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~bing-search-scraper---low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-bing-search-scraper---low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~bing-search-scraper---low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-bing-search-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~bing-search-scraper---low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-bing-search-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords", "TIME_FILTER", "MAX_ITEMS_PER_KEYWORD" ], "properties": { "keywords": { "title": "Keywords or subjects you wish to search for πŸ”πŸ“°", "type": "array", "description": "List of keywords or subjects to search for. Each keyword will be scraped separately.", "items": { "type": "string" }, "default": [ "Web", "Nature" ] }, "TIME_FILTER": { "title": "Time Filter", "enum": [ "any", "day", "week", "month", "year" ], "type": "string", "description": "Filter results by date", "default": "any" }, "MAX_ITEMS_PER_KEYWORD": { "title": "Max Items Per Keyword", "type": "integer", "description": "Maximum number of results to extract per keyword", "default": 30 } } }, "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 } } } } } } } } } } ```