# LinkedIn Ad Library Scraper (`codingfrontend/linkedin-ad-library-scraper`) Actor A fast, high-performance scraper built for lead generation, competitor analysis, and business intelligence. Extracts detailed business profiles, including name, contact details, emails, phone numbers, location, ratings, and reviews from LinkedIn. Supports custom search URLs, proxy rotation, and p... - **URL**: https://apify.com/codingfrontend/linkedin-ad-library-scraper.md - **Developed by:** [codingfrontend](https://apify.com/codingfrontend) (community) - **Categories:** Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## LinkedIn Ad Library Scraper Apify actor to scrape ad listings from the [LinkedIn Ad Library](https://www.linkedin.com/ad-library/search) based on search queries. ### Features - Search LinkedIn Ad Library by keyword or advertiser name - Filter ads by country/region - Extract advertiser names, ad text, dates, impressions, and media type - Automatic scrolling to load lazy-loaded results - Pagination support for multi-page results - Proxy support (residential proxies recommended) ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `query` | string | `"Google"` | Keyword or advertiser name to search for | | `maxItems` | integer | `50` | Maximum number of ad results to scrape (1–5000) | | `country` | string | `"US"` | Country code to filter ads by (e.g. US, GB, IN, DE) | | `proxyConfiguration` | object | Apify Residential | Proxy settings for the scraper | #### Example Input ```json { "query": "Google", "maxItems": 10, "country": "US" } ```` ### Output Each scraped ad contains: | Field | Type | Description | |-------|------|-------------| | `position` | integer | Result position index | | `advertiserName` | string | Name of the advertiser | | `adText` | string | Text content of the ad | | `startDate` | string | Date the ad started running | | `endDate` | string | Date the ad stopped running | | `impressions` | string | Impression count or range | | `link` | string | URL to the ad entry in LinkedIn Ad Library | | `mediaType` | string | Type of ad creative (Text, Image, Video) | | `query` | string | The search query used | | `country` | string | The country filter used | | `scrapedAt` | string | ISO timestamp of when the data was scraped | #### Example Output ```json { "position": 1, "advertiserName": "Google", "adText": "Build what's next with Google Cloud. Get started free.", "startDate": "Jan 2025", "endDate": "", "impressions": "100K-500K", "link": "https://www.linkedin.com/ad-library/detail/12345", "mediaType": "Image", "query": "Google", "country": "US", "scrapedAt": "2025-01-25T10:30:00.000Z" } ``` ### Usage #### Apify Console 1. Go to the actor's page on Apify Console 2. Set the input parameters 3. Click "Start" #### API ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('your-username/linkedin-ad-library-scraper').call({ query: 'Google', maxItems: 50, country: 'US', }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Local Development ```bash npm install npm start ``` ### Project Structure ``` src/ ├── main.js ## Actor entry point — reads input, configures crawler ├── constants.js ## Shared constants (URLs, scroll limits) ├── routes.js ## Crawler route handlers (SEARCH) └── utils/ └── extraction.js ## Ad data extraction from page DOM ``` # Actor input Schema ## `query` (type: `string`): The keyword or advertiser name to search for in the LinkedIn Ad Library. ## `maxItems` (type: `integer`): Maximum number of ad results to scrape. ## `country` (type: `string`): Country code to filter ads by (e.g. US, GB, IN, DE). ## `proxyConfiguration` (type: `object`): Proxy settings for the scraper. Use Apify residential proxies for best results. ## Actor input object example ```json { "query": "Google", "maxItems": 50, "country": "US", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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": "Google", "maxItems": 50, "country": "US" }; // Run the Actor and wait for it to finish const run = await client.actor("codingfrontend/linkedin-ad-library-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": "Google", "maxItems": 50, "country": "US", } # Run the Actor and wait for it to finish run = client.actor("codingfrontend/linkedin-ad-library-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": "Google", "maxItems": 50, "country": "US" }' | apify call codingfrontend/linkedin-ad-library-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codingfrontend/linkedin-ad-library-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Ad Library Scraper", "description": "A fast, high-performance scraper built for lead generation, competitor analysis, and business intelligence. Extracts detailed business profiles, including name, contact details, emails, phone numbers, location, ratings, and reviews from LinkedIn. Supports custom search URLs, proxy rotation, and p...", "version": "1.0", "x-build-id": "wY7yOUeUJuVdeivDm" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codingfrontend~linkedin-ad-library-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codingfrontend-linkedin-ad-library-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codingfrontend~linkedin-ad-library-scraper/runs": { "post": { "operationId": "runs-sync-codingfrontend-linkedin-ad-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codingfrontend~linkedin-ad-library-scraper/run-sync": { "post": { "operationId": "run-sync-codingfrontend-linkedin-ad-library-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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" ], "properties": { "query": { "title": "Search Query", "type": "string", "description": "The keyword or advertiser name to search for in the LinkedIn Ad Library.", "default": "Google" }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of ad results to scrape.", "default": 50 }, "country": { "title": "Country", "type": "string", "description": "Country code to filter ads by (e.g. US, GB, IN, DE).", "default": "US" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the scraper. Use Apify residential proxies for best results.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```