# Greenhouse, Lever & Ashby ATS Jobs Scraper (All-in-One API) (`velodata-labs/ats-jobs-scraper`) Actor

Fast, unified B2B ATS job board scraper for Greenhouse, Ashby, and Lever built in Golang. Extract active job postings, salary/compensation ranges, remote status, departments, and direct apply links from any company career page or slug. MCP-ready for Clay, n8n, and Make.

- **URL**: https://apify.com/velodata-labs/ats-jobs-scraper.md
- **Developed by:** [VeloData Labs](https://apify.com/velodata-labs) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 job & compensation 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Greenhouse, Lever & Ashby ATS Jobs Scraper (All-in-One API)

Extract active job postings, disclosed salary/compensation bands, remote work eligibility, departments, and direct application links across **Greenhouse**, **Ashby**, and **Lever** job boards in one unified dataset.

Built in **Golang** as a lightweight static binary (`128 MB` RAM) with sub-second response times, zero headless browser overhead, and full **Model Context Protocol (MCP)** compatibility for **Clay**, **n8n**, **Make**, **Zapier**, and AI recruiting agents.

***

### Why Use This ATS Jobs Scraper?

- **3 Major ATS Platforms in 1 Unified Schema**: Automatically detects and extracts job boards hosted on **Greenhouse** (`boards.greenhouse.io`), **Ashby** (`jobs.ashbyhq.com`), and **Lever** (`jobs.lever.co`).
- **Auto-Detection from Company Slug**: Pass a simple company slug like `openai`, `anthropic`, `stripe`, `palantir`, `cloudflare`, or `linear` — or pass explicit `ashby:openai`, `greenhouse:stripe`, `lever:palantir` targets or full URLs.
- **Disclosed Compensation & Equity Extraction**: Extracts structured `salaryMin`, `salaryMax`, `salaryCurrency`, `salarySummary`, and `offersEquity` directly from Ashby compensation tiers, Lever salary ranges, and Greenhouse pay transparency disclosures.
- **Built for B2B Lead Gen & Recruiting Workflows**: Filter by `keyword`, `location`, `remoteOnly`, or `onlyWithSalary` to build targeted hiring-signal feeds in **Clay** or **n8n**.

***

### Input Parameters

| Field | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `targets` | `array` | `["openai", "anthropic", "palantir"]` | Company slugs (`openai`, `stripe`), `ats:slug` pairs (`ashby:linear`, `greenhouse:cloudflare`, `lever:zoox`), or full ATS board URLs. |
| `keyword` | `string` | `""` | Optional case-insensitive filter for job title, department, or team (e.g., `engineer`, `security`, `ai`). |
| `location` | `string` | `""` | Optional location filter (e.g., `San Francisco`, `New York`, `London`, `Remote`). |
| `remoteOnly` | `boolean` | `false` | Return only remote-eligible job postings. |
| `onlyWithSalary` | `boolean` | `false` | Return only job postings with disclosed compensation/salary figures. |
| `includeDescription` | `boolean` | `true` | Include clean plain-text job descriptions in the output. |
| `maxItems` | `integer` | `50` | Maximum number of job listings to return across all targets. |

***

### Sample Output JSON

```json
{
  "jobId": "4747585e-c075-4d8e-8107-8903aa77f4a9",
  "atsPlatform": "ashby",
  "companySlug": "openai",
  "companyName": "Openai",
  "title": "Research Engineer, Post-Training",
  "department": "Research",
  "team": "Post-Training",
  "employmentType": "FullTime",
  "workplaceType": "OnSite",
  "isRemote": false,
  "location": "San Francisco",
  "allLocations": ["San Francisco"],
  "country": "US",
  "salaryMin": 250000,
  "salaryMax": 445000,
  "salaryCurrency": "USD",
  "salaryInterval": "1 YEAR",
  "salarySummary": "$250K – $445K • Offers Equity",
  "offersEquity": true,
  "jobUrl": "https://jobs.ashbyhq.com/openai/4747585e-c075-4d8e-8107-8903aa77f4a9",
  "applyUrl": "https://jobs.ashbyhq.com/openai/4747585e-c075-4d8e-8107-8903aa77f4a9/application",
  "publishedAt": "2026-10-15T18:22:10.000+00:00",
  "scrapedAt": "2026-11-03T06:50:00Z"
}
```

***

### Integrations: Clay, n8n, Make & AI Agents (MCP)

1. **Clay Hiring Signal Enrichment**: Trigger this Actor on target accounts to identify active engineering, security, or GTM hiring velocity along with salary budgets.
2. **n8n / Make Automation**: Schedule daily runs to track new openings across your watchlist of high-growth startups and pipe them to Slack, Notion, Airtable, or HubSpot.
3. **Model Context Protocol (MCP)**: Connect directly to Claude Desktop, Cursor, or Windsurf via Apify's MCP Server to query live job openings and salary ranges on demand.

# Actor input Schema

## `targets` (type: `array`):

List of company slugs, 'ats:slug' pairs, or full ATS URLs to scrape. Examples: 'openai', 'anthropic', 'stripe', 'palantir', 'ashby:linear', 'greenhouse:cloudflare', 'lever:zoox', or 'https://jobs.ashbyhq.com/openai'. Auto-detects Greenhouse, Ashby, and Lever.

## `keyword` (type: `string`):

Case-insensitive keyword filter matched against job title, department, team, or location (e.g., 'engineer', 'product', 'security', 'ai').

## `location` (type: `string`):

Case-insensitive filter for job location (e.g., 'San Francisco', 'New York', 'London', 'Singapore', 'Remote').

## `remoteOnly` (type: `boolean`):

When enabled, only returns jobs marked as remote or with 'Remote' in the location/workplace type.

## `onlyWithSalary` (type: `boolean`):

When enabled, only returns job postings that include salary or compensation range data.

## `includeDescription` (type: `boolean`):

Include clean plain-text job description in the output dataset.

## `maxItems` (type: `integer`):

Maximum number of job postings to return across all targets.

## Actor input object example

```json
{
  "targets": [
    "openai",
    "anthropic",
    "palantir"
  ],
  "remoteOnly": false,
  "onlyWithSalary": false,
  "includeDescription": true,
  "maxItems": 50
}
```

# Actor output Schema

## `jobs` (type: `string`):

Unified JSON/CSV dataset of job listings including company, ATS platform, title, department, location, remote status, compensation/salary range, and direct application URLs.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "targets": [
        "openai",
        "anthropic",
        "palantir"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("velodata-labs/ats-jobs-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "targets": [
        "openai",
        "anthropic",
        "palantir",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("velodata-labs/ats-jobs-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "targets": [
    "openai",
    "anthropic",
    "palantir"
  ]
}' |
apify call velodata-labs/ats-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,velodata-labs/ats-jobs-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/wcwrdrKXv4tuY8UXj/builds/MPZKWAjrpsRpLF9IL/openapi.json