# Indeed Jobs Scraper (`databro/indeedjobsscraper`) Actor Crawls Indeed job postings and extracts job title, company name, company logo, company website, location, location type (on-site, remote, etc.), country, date posted, valid through, employment type, salary range (min, max, currency, unit), and job description. - **URL**: https://apify.com/databro/indeedjobsscraper.md - **Developed by:** [Data Bro](https://apify.com/databro) (community) - **Categories:** Jobs, Lead generation - **Stats:** 101 total users, 0 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: 1.11 out of 5 stars ## Pricing $14.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Indeed Jobs Scraper 📄💼 Extract structured job listings from Indeed with detailed metadata including company info, salary breakdowns, employment types, and more — in blazing-fast speed using Scrapy! ⚡ --- ### 🔍 Input Example ````json { "searchKeyword": "Python Developer", "maxItems": 50, "location": "Remote" } ### Output Sample: ```json { "title": "Python Developer", "company": "Tech Solutions Inc.", "companyLogo": "https://example.com/logo.png", "company_website": "https://www.techsolutions.com", "location": "New York, NY", "locationType": "Remote", "country": "US", "date_posted": "2025-04-05", "valid_through": "2025-05-01", "employment_type": "Full-time, Contract", "salary": { "min": 6000, "max": 8000, "currency": "USD", "unit": "MONTH" }, "description": "We are looking for an experienced Python Developer to build backend services..." } ````` ### Why choose us Over other Actors on APIFY - This actor is fastest and also cheapest among all since it uses Scrapy to extract data and extracts hundreds of rows of data Parallely in seconds. - It uses very complex antibot bypass mechanism which enables it to scrape data without getting blocked ever. - Other actors use slow methods like Selenium or Headless browsers which are unreliable, slow and costly as well since they consume too much of resource. - We test our actors everyday to make sure your integrations keep running smoothly 24/7. - Extract data in any format or integrate it easily with your API. ### Features ✨ Scrapes job data from Indeed using keyword and location filters. Outputs a structured dataset ideal for analytics, dashboards, or integration. Supports pagination and limit configuration. Extracts: Job title, company name, logo, and company website Job location and remote/on-site status Posting date and validity date Employment type (full-time, contract, internship, etc.) Salary range with currency and unit Enriched job description 📋 Usage Just provide a job keyword, target location, and max number of listings — this actor handles the rest! # Actor input Schema ## `searchkeyword` (type: `string`): Job query to search for on the page. ## `location` (type: `string`): Get jobs from specific location only ## `maxItems` (type: `integer`): Maximum number of items ## Actor input object example ```json { "searchkeyword": "Web Developer", "location": "US", "maxItems": 20 } ``` # 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 = { "searchkeyword": "Web Developer", "location": "US", "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("databro/indeedjobsscraper").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 = { "searchkeyword": "Web Developer", "location": "US", "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("databro/indeedjobsscraper").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 '{ "searchkeyword": "Web Developer", "location": "US", "maxItems": 20 }' | apify call databro/indeedjobsscraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=databro/indeedjobsscraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Indeed Jobs Scraper", "description": "Crawls Indeed job postings and extracts job title, company name, company logo, company website, location, location type (on-site, remote, etc.), country, date posted, valid through, employment type, salary range (min, max, currency, unit), and job description.", "version": "0.0", "x-build-id": "uy3i7OsMEW7o3UfVl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/databro~indeedjobsscraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-databro-indeedjobsscraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/databro~indeedjobsscraper/runs": { "post": { "operationId": "runs-sync-databro-indeedjobsscraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/databro~indeedjobsscraper/run-sync": { "post": { "operationId": "run-sync-databro-indeedjobsscraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchkeyword", "location" ], "properties": { "searchkeyword": { "title": "searchkeyword", "type": "string", "description": "Job query to search for on the page.", "default": "Web Developer" }, "location": { "title": "Location", "type": "string", "description": "Get jobs from specific location only", "default": "US" }, "maxItems": { "title": "maxItems", "type": "integer", "description": "Maximum number of items", "default": 20 } } }, "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 } } } } } } } } } } ```