# Greenhouse Jobs Scraper - Jobs from Greenhouse Boards (`nabeelbaghoor/jobflow-greenhouse`) Actor Live jobs pulled directly from public Greenhouse career boards. Filter by keyword, title, location, remote, and date. Pay per result. - **URL**: https://apify.com/nabeelbaghoor/jobflow-greenhouse.md - **Developed by:** [Nabeel Hassan](https://apify.com/nabeelbaghoor) (community) - **Categories:** Jobs, Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $4.00 / 1,000 job results 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Greenhouse Jobs **Greenhouse Jobs** returns clean, structured job listings sourced directly from Greenhouse public job boards. Results are normalized to one schema, deduplicated, and filterable by keyword, title, location, workplace type, and date. You pay only for the results you receive. ### What you get per job - Job title, company, and location - Direct application link - Posting date - Source platform - Description snippet ### How it works This actor pulls live postings from public applicant tracking system boards, the same feeds companies publish for their own careers pages. No account or key required. ### Example input ```json { "keywords": ["engineer"], "locationTypes": ["Remote"], "maxResults": 100 } ```` ### Pricing Pay per result. You are charged a small fixed amount for each job returned, and standard Apify platform usage is included. Set Maximum results to cap the cost of any run. ### FAQ **Where does the data come from?** Directly from the public job board APIs that companies use to publish their open roles. **Can I target specific companies?** Yes. Add board slugs in the Specific companies field, or leave it empty to use our maintained directory. **Is there a result cap?** Yes, up to 5,000 results per run. # Actor input Schema ## `keywords` (type: `array`): Match against job title and description, e.g. `engineer`, `python`. Leave empty for all jobs. ## `jobTitles` (type: `array`): Match against the job title only, e.g. `Software Engineer`. ## `locationTypes` (type: `array`): Remote only, or leave empty for all. ## `countries` (type: `array`): Match location text, e.g. `United States`, `London`. ## `postedWithinDays` (type: `integer`): E.g. `7` for the last week. Leave empty for all time. ## `maxResults` (type: `integer`): Stop after this many jobs (1 to 5,000). Charged per result returned. ## `sortBy` (type: `string`): Order of results. ## Actor input object example ```json { "keywords": [ "engineer" ], "maxResults": 100, "sortBy": "date" } ``` # 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": [ "engineer" ], "maxResults": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("nabeelbaghoor/jobflow-greenhouse").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 = { "keywords": ["engineer"], "maxResults": 100, } # Run the Actor and wait for it to finish run = client.actor("nabeelbaghoor/jobflow-greenhouse").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 '{ "keywords": [ "engineer" ], "maxResults": 100 }' | apify call nabeelbaghoor/jobflow-greenhouse --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nabeelbaghoor/jobflow-greenhouse", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Greenhouse Jobs Scraper - Jobs from Greenhouse Boards", "description": "Live jobs pulled directly from public Greenhouse career boards. Filter by keyword, title, location, remote, and date. Pay per result.", "version": "0.1", "x-build-id": "Ndy8jAHOa3v7GUknw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nabeelbaghoor~jobflow-greenhouse/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nabeelbaghoor-jobflow-greenhouse", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nabeelbaghoor~jobflow-greenhouse/runs": { "post": { "operationId": "runs-sync-nabeelbaghoor-jobflow-greenhouse", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nabeelbaghoor~jobflow-greenhouse/run-sync": { "post": { "operationId": "run-sync-nabeelbaghoor-jobflow-greenhouse", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keywords": { "title": "Keywords", "type": "array", "description": "Match against job title and description, e.g. `engineer`, `python`. Leave empty for all jobs.", "items": { "type": "string" } }, "jobTitles": { "title": "Job titles", "type": "array", "description": "Match against the job title only, e.g. `Software Engineer`.", "items": { "type": "string" } }, "locationTypes": { "title": "Workplace type", "type": "array", "description": "Remote only, or leave empty for all.", "items": { "type": "string", "enum": [ "Remote", "Hybrid", "In-Person" ] } }, "countries": { "title": "Countries / locations", "type": "array", "description": "Match location text, e.g. `United States`, `London`.", "items": { "type": "string" } }, "postedWithinDays": { "title": "Posted within the last N days", "minimum": 1, "maximum": 365, "type": "integer", "description": "E.g. `7` for the last week. Leave empty for all time." }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Stop after this many jobs (1 to 5,000). Charged per result returned." }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date" ], "type": "string", "description": "Order of results.", "default": "date" } } }, "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 } } } } } } } } } } ```