# Multi-ATS Jobs Scraper (Greenhouse, Lever, Ashby) (`alwaysprimedev/multi-ats-jobs-scraper`) Actor Scrape job postings from Greenhouse, Lever, and Ashby into one unified, structured dataset. No login. Salary, location, department, employment type โ€” normalized across all three ATS. Per-company change-detection between runs. - **URL**: https://apify.com/alwaysprimedev/multi-ats-jobs-scraper.md - **Developed by:** [Always Prime](https://apify.com/alwaysprimedev) (community) - **Categories:** Jobs, SEO tools, Automation - **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 jobs 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 ## ๐Ÿค– Multi-ATS Jobs Scraper โ€” Greenhouse ยท Lever ยท Ashby [![Python](https://img.shields.io/badge/python-3.11-blue)](https://www.python.org/) [![Apify](https://img.shields.io/badge/Apify-actor-violet)](https://apify.com/) [![Output](https://img.shields.io/badge/output-JSON%20ยท%20CSV%20ยท%20Excel-green)](#sample-output) **One actor, three ATS, one unified schema.** Scrape job postings from **Greenhouse**, **Lever**, and **Ashby** in a single run โ€” every record is the same shape, no matter which ATS hosted it. Salary, location, department, employment type โ€” all normalized. โšก๏ธ Fast (no browser, pure HTTP) ยท ๐Ÿš€ Cheap (256 MB image) ยท ๐Ÿ“ฆ Three output formats ยท ๐Ÿ†• Built-in change-detection between runs. --- ### ๐ŸŽฏ Why this scraper - **Unified schema across three ATS.** Filter, dedupe, and join on the same fields whether the job came from Greenhouse, Lever, or Ashby. No more ATS-specific glue code. - **Salary normalization.** `salary_min`, `salary_max`, `salary_currency`, `salary_period` populated from the cleanest source each ATS exposes (JSON-LD on Ashby, regex-best-effort on Greenhouse and Lever). - **Change-detection.** Toggle `onlyNewSinceLastRun` and each subsequent run pushes only **new** jobs (`is_new: true`) and **closed** jobs (`is_closed: true`). Perfect for nightly diffs. - **Incremental mode.** Filter by `since` to skip jobs older than your last sync. - **Stable IDs.** Every record has a global ID `{ats}:{company_slug}:{job_id}` โ€” diff, join, and dedupe across runs without ambiguity. - **Multi-company in one run.** Drop a list of slugs per ATS and the actor fans out concurrently. --- ### ๐Ÿš€ Quick start 1. **Try for free** โ€” click the green Try for free button on this page. 2. **Pick your companies** โ€” paste each company's slug into Greenhouse / Lever / Ashby fields. (See FAQ for how to find a slug.) 3. **Start** โ€” click Start and watch the live log. 4. **Download** โ€” once the run finishes, grab the dataset as **JSON**, **CSV**, or **Excel** (or open it in the Apify Console). --- ### โš™๏ธ Input fields | Field | Type | Default | Description | |---|---|---|---| | `greenhouseCompanies` | list of strings | `[]` | Greenhouse slugs (e.g. `airbnb`, `stripe`, `discord`). Find at `boards.greenhouse.io/`. | | `leverCompanies` | list of strings | `[]` | Lever slugs (e.g. `palantir`, `mixpanel`, `netflix`). Find at `jobs.lever.co/`. | | `ashbyCompanies` | list of strings | `[]` | Ashby slugs (e.g. `ramp`, `linear`, `vercel`). Find at `jobs.ashbyhq.com/`. | | `maxItems` | integer | `0` (unlimited) | Stop after this many records across all companies. Useful for testing or daily caps. | | `includeDescriptionHtml` | boolean | `true` | Drop full HTML descriptions to shrink dataset by ~70-90%. | | `includeDescriptionText` | boolean | `true` | Drop plaintext descriptions. | | `since` | datetime | โ€” | Skip jobs published/updated before this date. ISO format. | | `onlyNewSinceLastRun` | boolean | `false` | Diff mode โ€” emit only new and closed jobs vs the previous run. | | `concurrency` | integer | `5` | In-flight HTTP requests cap. Hard cap 25. | --- ### ๐Ÿ“ฆ Sample output ```json { "id": "ashby:ramp:8c004352-f162-4d89-858f-75a649e77ec4", "ats": "ashby", "company_slug": "ramp", "company_name": "Ramp", "job_id": "8c004352-f162-4d89-858f-75a649e77ec4", "title": "Account Executive | Commercial", "url": "https://jobs.ashbyhq.com/ramp/8c004352-f162-4d89-858f-75a649e77ec4", "apply_url": "https://jobs.ashbyhq.com/ramp/8c004352-f162-4d89-858f-75a649e77ec4", "description_html": "

About Ramp

...", "description_text": "About Ramp Ramp is building the smart infrastructure...", "department": "Sales", "teams": ["Sales", "Account Executive"], "location": "New York, NY (HQ)", "secondary_locations": ["San Francisco, CA"], "country": "US", "workplace_type": "hybrid", "employment_type": "full_time", "salary_min": 144000, "salary_max": 220000, "salary_currency": "USD", "salary_period": "year", "salary_summary": "$144K โ€“ $220K โ€ข Offers Equity โ€ข Offers Commission โ€ข Multiple Ranges", "published_at": "2025-10-09", "updated_at": null, "application_deadline": null, "is_new": false, "is_closed": false, "scraped_at": "2026-05-10T18:00:00Z" } ```` *** ### ๐Ÿ’ผ Use cases | Who | What for | |---|---| | ๐Ÿค– **AI-recruiter SaaS** | Feed candidates fresh openings across the YC/SaaS company list with a single API. | | ๐ŸŽฏ **Niche job boards** | Power vertical job boards (DevOps, FinTech, Climate, etc.) with a curated company list โ€” one ETL, three ATS covered. | | ๐Ÿ” **Executive search firms** | Track movement at competitor companies โ€” new VP-level roles, closed CFO searches โ€” via the diff mode. | | ๐Ÿ“Š **Wage / market researchers** | Build salary distributions over time. With `onlyNewSinceLastRun`, you get an append-only event log of postings and their compensation. | | ๐Ÿง  **ML / NLP teams** | Title-to-skill, JD-to-skill, salary-prediction datasets. Same schema across three ATS = no normalization preprocessing. | | ๐Ÿ› ๏ธ **HR-tech tooling** | Embed real openings in your product without each customer having to integrate with three different ATS APIs.| *** ### ๐Ÿ’ก Tips & tricks - **Building a company list?** Run with `maxItems: 1` for each candidate slug to verify the slug is correct before committing to a full scrape. - **Daily incremental runs:** schedule the actor with `onlyNewSinceLastRun: true`. The first run takes a snapshot; subsequent runs emit only new and closed jobs. Combine with Apify's webhooks for real-time recruiting alerts. - **Cheap diff scans:** set `includeDescriptionHtml: false` and `includeDescriptionText: false` to drop ~80% of the bytes when you only care about which roles exist, not the full JD. - **Cross-ATS dedupe:** use the `id` field (`{ats}:{slug}:{job_id}`). Same role posted to two ATS โ†’ two records with different IDs, but same `title`+`company_slug` lets you cluster them. - **Large companies:** Greenhouse and Lever return all jobs in one request; even a 500-job catalog takes < 5 seconds. Ashby fetches one detail per job, so a 200-job Ashby company is the slowest path (~30-60 seconds). *** ### โ“ FAQ **Q: How do I find a company's slug?** A: Visit their public careers page. The URL will be one of: - `boards.greenhouse.io/` or `.greenhouse.io` โ†’ **Greenhouse** - `jobs.lever.co/` โ†’ **Lever** - `jobs.ashbyhq.com/` โ†’ **Ashby** The `` part is what you put in the input field. **Q: Why are some salary fields null?** A: Salary transparency varies by company and jurisdiction. Ashby exposes structured comp via JSON-LD when the company posts it. Greenhouse and Lever rely on free-text in the description, which we parse on a best-effort basis. When parsing isn't confident, we leave the structured fields null and put the original text in `salary_summary`. **Q: What does `maxItems` actually cap?** A: Total records pushed to the dataset, across all ATS. If you ask for `maxItems: 50` with three ATS configured, the run stops at 50 total โ€” first-come-first-served. For balanced sampling across ATS, run with `maxItems: 0` (unlimited) and post-filter. **Q: How does change-detection work?** A: With `onlyNewSinceLastRun: true`, the actor stores a snapshot of seen IDs in its key-value store (`SEEN_JOBS`). On the next run: - IDs not in the snapshot โ†’ pushed with `is_new: true`. - IDs in the snapshot but missing this run โ†’ pushed as stub records with `is_closed: true`. - IDs present in both โ†’ skipped entirely (already had them). The first run is always a "full scan" because there's no prior snapshot. **Q: Can I scrape Workable too?** A: Workable is on the v0.2 roadmap. Their public job-board API needs a different infrastructure setup than the other three ATS. Coming soon. **Q: What's the rate limit?** A: We respect each ATS's published guidance โ€” Lever's `Crawl-delay: 1` from `robots.txt` is honored automatically. Greenhouse and Ashby have no published limits. We default to 5 concurrent in-flight requests; you can lower it if you're scraping hundreds of companies. *** ### ๐Ÿ’ฐ Pricing This actor is **pay-per-result**: you're charged once per successfully scraped job posting (`job-scraped` event). No charge for failed companies, deduplicated records, or `is_closed` stubs. Try-for-free credits cover ~3,000 jobs. *** ### ๐Ÿ”— Roadmap - v0.2 โ€” Workable support (residential infrastructure) - v0.2 โ€” auto-detect ATS from a careers URL (paste `careers.acme.com`, we figure out the rest) - v0.3 โ€” curated company registry as a separate actor (1,000+ pre-tagged companies grouped by industry) - v0.3 โ€” webhook-friendly diff mode (push only changes to a URL of your choice) *** Built on the [Apify platform](https://apify.com/). # Actor input Schema ## `greenhouseCompanies` (type: `array`): List of Greenhouse company slugs to scrape (the part after `/v1/boards/` in the public board URL, e.g. `airbnb`, `stripe`, `discord`). Find the slug at boards.greenhouse.io/. ## `leverCompanies` (type: `array`): List of Lever company slugs to scrape (the part after jobs.lever.co/, e.g. `palantir`, `mixpanel`, `netflix`). ## `ashbyCompanies` (type: `array`): List of Ashby company slugs to scrape (the part after jobs.ashbyhq.com/, e.g. `ramp`, `linear`, `vercel`). ## `maxItems` (type: `integer`): Stop after pushing this many job records across all companies and ATS. Use 0 for unlimited. ## `includeDescriptionHtml` (type: `boolean`): If false, drops `description_html` from each record. Reduces dataset size by 70-90%. ## `includeDescriptionText` (type: `boolean`): If false, drops `description_text` from each record. ## `since` (type: `string`): ISO date or datetime. Records older than this are skipped at push-time. Useful for daily incremental runs. ## `onlyNewSinceLastRun` (type: `boolean`): Persists a snapshot of seen job IDs in the actor's key-value store and emits each subsequent run only as a diff: new jobs (`is_new: true`) and closed jobs (`is_closed: true`). Off on first run. ## `concurrency` (type: `integer`): Maximum number of in-flight HTTP requests across all ATS. Higher = faster but more memory and more chance of triggering rate limits. Default 5, hard cap 25. ## Actor input object example ```json { "greenhouseCompanies": [ "airbnb" ], "leverCompanies": [], "ashbyCompanies": [], "maxItems": 100, "includeDescriptionHtml": true, "includeDescriptionText": true, "since": "2026-04-01", "onlyNewSinceLastRun": false, "concurrency": 5 } ``` # Actor output Schema ## `jobs` (type: `string`): No description ## `jobsCsv` (type: `string`): No description ## `jobsXlsx` (type: `string`): No description ## `consoleView` (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 = { "greenhouseCompanies": [ "airbnb" ], "leverCompanies": [], "ashbyCompanies": [], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("alwaysprimedev/multi-ats-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "greenhouseCompanies": ["airbnb"], "leverCompanies": [], "ashbyCompanies": [], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("alwaysprimedev/multi-ats-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "greenhouseCompanies": [ "airbnb" ], "leverCompanies": [], "ashbyCompanies": [], "maxItems": 100 }' | apify call alwaysprimedev/multi-ats-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=alwaysprimedev/multi-ats-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Multi-ATS Jobs Scraper (Greenhouse, Lever, Ashby)", "description": "Scrape job postings from Greenhouse, Lever, and Ashby into one unified, structured dataset. No login. Salary, location, department, employment type โ€” normalized across all three ATS. Per-company change-detection between runs.", "version": "0.1", "x-build-id": "gFr92eHEOVHVjY3kB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/alwaysprimedev~multi-ats-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-alwaysprimedev-multi-ats-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/alwaysprimedev~multi-ats-jobs-scraper/runs": { "post": { "operationId": "runs-sync-alwaysprimedev-multi-ats-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/alwaysprimedev~multi-ats-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-alwaysprimedev-multi-ats-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "greenhouseCompanies": { "title": "Greenhouse companies", "type": "array", "description": "List of Greenhouse company slugs to scrape (the part after `/v1/boards/` in the public board URL, e.g. `airbnb`, `stripe`, `discord`). Find the slug at boards.greenhouse.io/.", "default": [], "items": { "type": "string" } }, "leverCompanies": { "title": "Lever companies", "type": "array", "description": "List of Lever company slugs to scrape (the part after jobs.lever.co/, e.g. `palantir`, `mixpanel`, `netflix`).", "default": [], "items": { "type": "string" } }, "ashbyCompanies": { "title": "Ashby companies", "type": "array", "description": "List of Ashby company slugs to scrape (the part after jobs.ashbyhq.com/, e.g. `ramp`, `linear`, `vercel`).", "default": [], "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 0, "type": "integer", "description": "Stop after pushing this many job records across all companies and ATS. Use 0 for unlimited.", "default": 0 }, "includeDescriptionHtml": { "title": "Include HTML description", "type": "boolean", "description": "If false, drops `description_html` from each record. Reduces dataset size by 70-90%.", "default": true }, "includeDescriptionText": { "title": "Include plaintext description", "type": "boolean", "description": "If false, drops `description_text` from each record.", "default": true }, "since": { "title": "Only jobs updated/published after", "type": "string", "description": "ISO date or datetime. Records older than this are skipped at push-time. Useful for daily incremental runs." }, "onlyNewSinceLastRun": { "title": "Only emit new and closed jobs vs last run", "type": "boolean", "description": "Persists a snapshot of seen job IDs in the actor's key-value store and emits each subsequent run only as a diff: new jobs (`is_new: true`) and closed jobs (`is_closed: true`). Off on first run.", "default": false }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 25, "type": "integer", "description": "Maximum number of in-flight HTTP requests across all ATS. Higher = faster but more memory and more chance of triggering rate limits. Default 5, hard cap 25.", "default": 5 } } }, "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 } } } } } } } } } } ```