# Indeed Salaries Scraper — Pay by Company & Role, No API Key (`jamhimself/indeed-salaries-scraper`) Actor Scrape Indeed salary data by company and job title as clean JSON. Get median pay, salaryAmount, pay period, and report counts per role. No API key, no login, bulk input, pay per result. - **URL**: https://apify.com/jamhimself/indeed-salaries-scraper.md - **Developed by:** [Jaime Martinez](https://apify.com/jamhimself) (community) - **Categories:** Lead generation, Agents, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $7.00 / 1,000 salary records 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 ## Indeed Salaries Scraper (No API Key) Scrape Indeed salary data by company and job title as clean, structured JSON — no API key, no login. Point this Indeed salaries scraper at any company's Indeed salaries page and it returns the median pay per role: `jobTitle`, `salaryDisplay`, parsed `salaryAmount`, `salaryType` (yearly/hourly), `reportedSalaryCount`, `currency`, and a `salaryUrl`. Built for developers, data analysts, recruiters, compensation and market-research teams, and AI/RAG pipelines that need bulk salary benchmarks. No API key, no login, bulk company input, pay per result. Reliability comes from Chrome TLS impersonation (curl_cffi) plus residential US proxies with per-request session rotation to clear Indeed's anti-bot walls and read Indeed's own server-embedded structured salary data. ### What you get Each row is one job title's salary aggregate for a company: | Field | Description | |---|---| | `company` | Company slug the salaries belong to | | `jobTitle` | The role / job title | | `salaryDisplay` | Salary as shown on Indeed, e.g. `$150,849` | | `salaryAmount` | Parsed numeric amount | | `salaryType` | Pay period (e.g. YEARLY / HOURLY) | | `reportedSalaryCount` | How many reported salaries the figure is based on | | `currency` | Currency code (defaults to USD) | | `salaryUrl` | Link to the role's salary detail on Indeed | ### Use cases - **Compensation benchmarking** — compare median pay by role across a set of companies to size offers and pay bands. - **Competitor and employer monitoring** — track salary ranges at competitors to inform hiring and retention strategy. - **Salary and labor-market research** — build datasets of pay by job title and company for analysis and reporting. - **Recruiter sourcing intelligence** — arm recruiters with real pay expectations by role before outreach. - **LLM / RAG feed** — pipe structured salary aggregates into vector stores so AI agents can answer "what does role X pay at company Y?" - **Dataset building** — assemble a reusable salary corpus by role and company for BI dashboards or spreadsheets. ### Input | Param | Type | Description | |---|---|---| | `startUrls` | array | One or more Indeed company salary pages. Prefill: `https://www.indeed.com/cmp/Amazon.com/salaries` | | `companies` | array | Alternative to `startUrls`: plain Indeed company slugs, e.g. `Amazon.com` | | `maxSalaries` | integer | Max salary rows per company. Default `500`, max `10000` | Example: ```json { "startUrls": [{ "url": "https://www.indeed.com/cmp/Amazon.com/salaries" }], "companies": ["Google", "Microsoft"], "maxSalaries": 500 } ```` ### Pricing Pay per salary row delivered. No subscription — you only pay for the rows you receive. If this Indeed salaries scraper saves you time, a quick review on the Apify Store is genuinely appreciated and helps others find it. # Actor input Schema ## `startUrls` (type: `array`): One or more Indeed company salary pages, e.g. https://www.indeed.com/cmp/Amazon.com/salaries ## `companies` (type: `array`): Alternative to startUrls: Indeed company slugs, e.g. "Amazon.com". ## `maxSalaries` (type: `integer`): Maximum per-job-title salary rows to return per company. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.indeed.com/cmp/Amazon.com/salaries" } ], "maxSalaries": 500 } ``` # Actor output Schema ## `salaries` (type: `string`): One row per job title: median pay, pay period, and number of reports. # 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 = { "startUrls": [ { "url": "https://www.indeed.com/cmp/Amazon.com/salaries" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("jamhimself/indeed-salaries-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 = { "startUrls": [{ "url": "https://www.indeed.com/cmp/Amazon.com/salaries" }] } # Run the Actor and wait for it to finish run = client.actor("jamhimself/indeed-salaries-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 '{ "startUrls": [ { "url": "https://www.indeed.com/cmp/Amazon.com/salaries" } ] }' | apify call jamhimself/indeed-salaries-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jamhimself/indeed-salaries-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Indeed Salaries Scraper — Pay by Company & Role, No API Key", "description": "Scrape Indeed salary data by company and job title as clean JSON. Get median pay, salaryAmount, pay period, and report counts per role. No API key, no login, bulk input, pay per result.", "version": "1.0", "x-build-id": "GoKroRo2cNnwmkUj9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jamhimself~indeed-salaries-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jamhimself-indeed-salaries-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jamhimself~indeed-salaries-scraper/runs": { "post": { "operationId": "runs-sync-jamhimself-indeed-salaries-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jamhimself~indeed-salaries-scraper/run-sync": { "post": { "operationId": "run-sync-jamhimself-indeed-salaries-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "startUrls": { "title": "Indeed company salary URLs", "type": "array", "description": "One or more Indeed company salary pages, e.g. https://www.indeed.com/cmp/Amazon.com/salaries", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "companies": { "title": "Company slugs (plain list)", "type": "array", "description": "Alternative to startUrls: Indeed company slugs, e.g. \"Amazon.com\".", "items": { "type": "string" } }, "maxSalaries": { "title": "Max salary rows per company", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum per-job-title salary rows to return per company.", "default": 500 } } }, "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 } } } } } } } } } } ```