# ATS Tech Stack Scraper (`devilscrapes/ats-tech-stack-scraper`) Actor
Extract company tech stacks from Greenhouse, Lever and Ashby job posts. Detects 100+ frameworks, databases and cloud platforms from live job descriptions. B2B sales intel without the $39-$399/mo SaaS bill.
- **URL**: https://apify.com/devilscrapes/ats-tech-stack-scraper.md
- **Developed by:** [DevilScrapes](https://apify.com/devilscrapes) (community)
- **Categories:** Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per event
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
## ATS Tech Stack Scraper
**๐ฐ $5.05 / 1 000 rows** ยท pay only for results ยท no credit card to try
_We do the dirty work so your dataset stays clean._ ๐
**B2B tech-stack intel from public job posts โ no $39-$399/mo SaaS bill.** Point this Actor at any company's Greenhouse, Lever or Ashby board and get one structured row per active job, including a deduplicated list of canonical tech names (Postgres, Django, AWS, Kubernetes...) detected directly from the job description.
Sales reps qualifying accounts, recruiters sourcing by skill, and competitive-intelligence analysts mapping vendor footprint all need this signal. Commercial tools (TheirStack, Wappalyzer, BuiltWith) charge subscription fees for the same data. This Actor hits the **public ATS APIs directly** โ no scraping, no browser, no auth โ and emits a flat, Pydantic-validated dataset ready for any CRM enrichment pipeline.
### ๐ฏ What this scrapes
Three ATS platforms, one schema:
1. **Greenhouse** โ `boards-api.greenhouse.io/v1/boards/{token}/jobs?content=true` (public, no auth)
2. **Lever** โ `api.lever.co/v0/postings/{token}` (public, no auth)
3. **Ashby** โ `api.ashbyhq.com/posting-api/job-board/{token}` (public, no auth; token is **case-sensitive** โ `Ramp`, not `ramp`)
For each active job posting the Actor pulls the title, location, department, full HTML/plain-text description, and the public URL โ then runs a case-insensitive word-boundary regex against a curated vocabulary of ~110 canonical tech names. The result is a single column you can pivot or filter without per-company string normalization.
| Field | Type | Description |
|---|---|---|
| `ats` | string | `greenhouse`, `lever`, or `ashby` |
| `company_token` | string | Board slug passed to the ATS |
| `job_id` | string | ATS-canonical job id |
| `title` | string | Job posting title |
| `location` | string \| null | Location string (Remote, NYC, Berlin...) |
| `department` | string \| null | Department / team |
| `url` | string | Public job-post URL |
| `description_text` | string | Plain-text description (HTML stripped) |
| `detected_techs` | string[] | Sorted, deduplicated canonical tech names |
| `posted_at` | string \| null | ISO 8601 UTC publication timestamp |
| `scraped_at` | string | ISO 8601 UTC row-creation timestamp |
### ๐ฅ Features
- **Three ATSs, one schema** โ Greenhouse, Lever, Ashby normalized to identical row shape.
- **Curated tech vocabulary** โ ~110 canonical names spanning languages (Python, Go, Rust), frameworks (Django, React, FastAPI), databases (Postgres, MongoDB, Redis, Snowflake), cloud (AWS, GCP, Azure, Vercel), infra (Kubernetes, Terraform, Docker), CI/CD, observability, and ML/data tools.
- **Per-company isolation** โ one bad token (404 from Lever, typo on Ashby) does not abort the run; the others still produce data.
- **No browser, no auth** โ pure HTTP with `curl-cffi` browser-TLS impersonation; low compute footprint and fast runs.
- **Pydantic v2 validation** โ every input and every output row is model-validated.
- **Filter knobs** โ `maxJobsPerCompany` cap and `minTechsDetected` floor.
- **Exponential backoff** on 429 / 503 with `Retry-After` honoured.
### ๐ก Use cases
- **B2B sales qualification** โ enrich every Salesforce/HubSpot account with the company's live tech stack: "they hire Django + Postgres + AWS" tells you whether to pitch your Postgres-tuning SaaS.
- **Recruiter sourcing** โ pull every "Senior Backend Engineer" role from your target accounts and filter by `detected_techs` to find teams that match your candidate's stack.
- **Competitive intelligence** โ track which competitors are hiring for `Kubernetes` or `Snowflake` and infer their roadmap.
- **CRM enrichment** โ replace TheirStack / BuiltWith / Wappalyzer subscriptions for the subset of buyers who publish their stack in JDs anyway.
- **Investment research** โ map private-company tech footprint over time without paying for a Crunchbase Pro seat.
- **Open-source stack maps** โ feed a public site that ranks the most-hired-for technologies in YC-backed startups.
### โ๏ธ How to use it
1. Open the Actor input form.
2. Add one or more `{companyToken, atsType}` pairs under **Companies to scrape** (the form prefills with `airtable` on Greenhouse and `Ramp` on Ashby).
3. (Optional) Set **Max jobs per company** โ leave empty for no cap.
4. (Optional) Set **Minimum detected techs** โ `2` or `3` drops generic/non-engineering postings.
5. Leave **Use Apify Proxy** off unless you observe rate-limiting (public ATS APIs do not require it).
6. Click **Start**. Rows stream into the default dataset.
#### Quick examples
**Two engineering-heavy companies, default settings:**
```json
{
"companies": [
{ "companyToken": "airtable", "atsType": "greenhouse" },
{ "companyToken": "Ramp", "atsType": "ashby" }
]
}
````
**Single Lever company, drop sales/marketing roles:**
```json
{
"companies": [
{ "companyToken": "palantir", "atsType": "lever" }
],
"minTechsDetected": 3
}
```
**Three companies across all three ATSs, capped at 50 jobs each:**
```json
{
"companies": [
{ "companyToken": "airtable", "atsType": "greenhouse" },
{ "companyToken": "palantir", "atsType": "lever" },
{ "companyToken": "Ramp", "atsType": "ashby" }
],
"maxJobsPerCompany": 50,
"minTechsDetected": 2
}
```
### Pricing (Pay-Per-Event)
| Event | Price | When |
|---|---|---|
| `actor-start` | $0.05 | Once per run |
| `result-row` | $0.005 | Per job row emitted |
A typical 50-job run costs `$0.05 + 50 ร $0.005 = $0.30`. Compare to TheirStack at $39-$399/month for the same signal.
### How to find a company's ATS token
- **Greenhouse**: the path segment in `boards.greenhouse.io/{token}` or `{token}.applytojob.com`. Examples: `airtable`, `figma`, `stripe`.
- **Lever**: the path segment in `jobs.lever.co/{token}`. Examples: `palantir`, `netflix`, `eventbrite`.
- **Ashby**: the path segment in `jobs.ashbyhq.com/{Token}`. **Case-sensitive** โ `Ramp`, `PostHog`, `Linear` work; the lowercase variants return zero jobs.
### Output and limits
- Rows are pushed to the default Apify dataset as they are produced โ long runs surface rows immediately.
- Apify FREE-tier default storage retains datasets for 7 days; use `Actor.open_dataset(name="...")` if you need to outlive that.
- The Actor exits successfully when at least one company yields one or more jobs. If every company returns zero (e.g. all tokens were misspelled), the run fails loud with a non-zero exit code.
### Notes and caveats
- Tech detection is regex-based, not LLM-based โ it is deterministic, free, and high-precision but will miss tools whose names are not in the curated vocabulary. Open a feedback request to add more.
- Greenhouse `content` is double-HTML-encoded (e.g. `<div>` for ``); the parser unescapes twice before stripping tags.
- Lever's `descriptionPlain` often omits the "Requirements" bullet list; the parser concatenates every `lists[].content` chunk so skills hidden there are still detected.
- Ashby exposes both `descriptionHtml` and `descriptionPlain` โ the parser prefers `descriptionPlain` when present.
### Related Actors
- **LLM Pricing Monitor** โ track live API pricing across OpenAI, Anthropic, Google, Mistral, Groq, Together AI, and DeepSeek in one normalized schema.
- **GitHub Org Scraper** โ pair tech-stack signals from JDs with actual code-repo activity per org.
- **Y Combinator Companies Scraper** โ combine YC funding signal with ATS-derived tech stack for a complete startup profile.
### Support
- Author: **DevilScrapes** ([profile](https://apify.com/DevilScrapes))
- Issues / feature requests: open a feedback ticket on the Actor's Apify Store page.
# Actor input Schema
## `companies` (type: `array`):
List of {companyToken, atsType} pairs. atsType is one of greenhouse, lever, ashby. companyToken is the board slug in the ATS URL (e.g. airtable for Greenhouse, palantir for Lever, Ramp for Ashby โ Ashby is case-sensitive).
## `maxJobsPerCompany` (type: `integer`):
Hard cap on rows emitted per company. Leave empty for no cap.
## `minTechsDetected` (type: `integer`):
Drop jobs whose detected\_techs list has fewer than this many entries. 0 keeps every job.
## `useProxy` (type: `boolean`):
Route requests via Apify Proxy (BUYPROXIES94952). All three ATS APIs are public โ only enable if you observe rate-limiting.
## Actor input object example
```json
{
"companies": [
{
"companyToken": "airtable",
"atsType": "greenhouse"
},
{
"companyToken": "Ramp",
"atsType": "ashby"
}
],
"minTechsDetected": 0,
"useProxy": false
}
```
# Actor output Schema
## `datasetItems` (type: `string`):
All dataset items as JSON.
## `datasetItemsCsv` (type: `string`):
Same data exported to CSV.
## `datasetView` (type: `string`):
Open the run dataset in the Console.
# 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 = {
"companies": [
{
"companyToken": "airtable",
"atsType": "greenhouse"
},
{
"companyToken": "Ramp",
"atsType": "ashby"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("devilscrapes/ats-tech-stack-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? 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 = { "companies": [
{
"companyToken": "airtable",
"atsType": "greenhouse",
},
{
"companyToken": "Ramp",
"atsType": "ashby",
},
] }
# Run the Actor and wait for it to finish
run = client.actor("devilscrapes/ats-tech-stack-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"companies": [
{
"companyToken": "airtable",
"atsType": "greenhouse"
},
{
"companyToken": "Ramp",
"atsType": "ashby"
}
]
}' |
apify call devilscrapes/ats-tech-stack-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=devilscrapes/ats-tech-stack-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "ATS Tech Stack Scraper",
"description": "Extract company tech stacks from Greenhouse, Lever and Ashby job posts. Detects 100+ frameworks, databases and cloud platforms from live job descriptions. B2B sales intel without the $39-$399/mo SaaS bill.",
"version": "0.1",
"x-build-id": "WmX22h7Cbv3rbWgAe"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/devilscrapes~ats-tech-stack-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-devilscrapes-ats-tech-stack-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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/devilscrapes~ats-tech-stack-scraper/runs": {
"post": {
"operationId": "runs-sync-devilscrapes-ats-tech-stack-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/devilscrapes~ats-tech-stack-scraper/run-sync": {
"post": {
"operationId": "run-sync-devilscrapes-ats-tech-stack-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",
"required": [
"companies"
],
"properties": {
"companies": {
"title": "Companies to scrape",
"type": "array",
"description": "List of {companyToken, atsType} pairs. atsType is one of greenhouse, lever, ashby. companyToken is the board slug in the ATS URL (e.g. airtable for Greenhouse, palantir for Lever, Ramp for Ashby โ Ashby is case-sensitive)."
},
"maxJobsPerCompany": {
"title": "Max jobs per company",
"minimum": 1,
"type": "integer",
"description": "Hard cap on rows emitted per company. Leave empty for no cap."
},
"minTechsDetected": {
"title": "Minimum detected techs",
"minimum": 0,
"type": "integer",
"description": "Drop jobs whose detected_techs list has fewer than this many entries. 0 keeps every job.",
"default": 0
},
"useProxy": {
"title": "Use Apify Proxy",
"type": "boolean",
"description": "Route requests via Apify Proxy (BUYPROXIES94952). All three ATS APIs are public โ only enable if you observe rate-limiting.",
"default": false
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```