# Wellfound Market Sizes by Industry, City and Tech (`gubidonius/wellfound-markets`) Actor

How many startups are hiring in each Wellfound industry, city and technology, and how many jobs each city holds. Sizes come from each segment's own page, not from counting rows. A slug Wellfound does not know returns its whole index, so this checks the filter the page applied before taking a number.

- **URL**: https://apify.com/gubidonius/wellfound-markets.md
- **Developed by:** [Gregory Bolshakov](https://apify.com/gubidonius) (community)
- **Categories:** Business, Lead generation, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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/actors/running/actors-in-store.md#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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Wellfound Market Sizes by Industry, City and Tech

Reads how big each Wellfound segment is. How many startups are hiring in an industry, a city or
around a technology, and how many open jobs a city holds. No key and no login.

### Where the numbers come from

Each segment has its own page on Wellfound, and that page prints its own total. This Actor
reads that total. It does not count rows and then call the count a size.

The segment list comes from Wellfound too, in two requests: the startup index lists about 30
industries and 30 cities, and the hiring data page lists 33 industries, 40 cities and 109
technologies. They are merged, so you get the wider list and the tagging counts that only one
of the two pages carries.

### A slug it does not know

Ask `/startups/industry/fintech` and Wellfound answers HTTP 200 with its whole index. The size
of fintech would come back as 10,367, which is the size of Wellfound.

The real slug is `fintech-2`. This Actor reads the filter the page says it applied, skips the
segment when it does not match, and charges you nothing for it. City pages behave differently
and answer 404, which is handled the same way.

### The tagging count is not a company count

`taggingsAcrossWellfound` is Wellfound's own popularity number for a tag, and it counts every
tagging on the site. For a technology that is mostly candidate profiles: Python reads over 1.7
million taggings and 2,642 companies.

Use `startupsHiring` for companies. Use the tagging count to rank a technology by how many
people on Wellfound claim it.

### The counts overlap

A company sits in several industries and several cities at once, so segment sizes do not add
up to the total. Wellfound's own index total moves between requests as well. Both numbers are
sizes, not a ledger.

### What this pairs with

`slug` on every row is exactly what the other Wellfound Actors take as a filter. Size the
segments here, then run the company or job Actor on the ones worth the money.

### Input

| Field | What it does |
|---|---|
| `kinds` | Which kinds to list automatically: industry, location, technology |
| `industries` | Name specific industries instead |
| `locations` | Name specific cities instead |
| `technologies` | Name specific technologies instead |
| `maxResults` | Upper bound for the whole run. One segment is one page load |

### Output

One row per segment: `kind`, `name`, `slug`, `startupsHiring`, `jobsOpen` for cities,
`taggingsAcrossWellfound` and the page it was read from.

`RUN_SUMMARY` in the key value store holds the discovery pages, how many segments were
considered against how many were sized, and every segment Wellfound did not recognise.

### Price

0.002 dollars per run and 0.006 dollars per segment. One segment is one page load. Both are
charged after the rows exist, so a run that sizes nothing costs nothing.

# Actor input Schema

## `kinds` (type: `array`):

Any of industry, location, technology. Used only when you name no segments below. Wellfound lists about 34 industries, 40 cities and 109 technologies.

## `industries` (type: `array`):

Specific industry slugs or links, for example enterprise-software. Naming any segment here turns off the automatic list.

## `locations` (type: `array`):

Specific city slugs or links, for example san-francisco, london.

## `technologies` (type: `array`):

Specific technology slugs or links, for example python, react.

## `maxResults` (type: `integer`):

Upper bound on segments for the WHOLE run. Each segment is one page load, so this is also the request count. You are never charged for more than this.

## Actor input object example

```json
{
  "kinds": [
    "industry",
    "location"
  ],
  "industries": [],
  "locations": [],
  "technologies": [],
  "maxResults": 25
}
```

# Actor output Schema

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

// Prepare Actor input
const input = {
    "kinds": [
        "industry",
        "location"
    ],
    "industries": [],
    "locations": [],
    "technologies": [],
    "maxResults": 25
};

// Run the Actor and wait for it to finish
const run = await client.actor("gubidonius/wellfound-markets").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 = {
    "kinds": [
        "industry",
        "location",
    ],
    "industries": [],
    "locations": [],
    "technologies": [],
    "maxResults": 25,
}

# Run the Actor and wait for it to finish
run = client.actor("gubidonius/wellfound-markets").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 '{
  "kinds": [
    "industry",
    "location"
  ],
  "industries": [],
  "locations": [],
  "technologies": [],
  "maxResults": 25
}' |
apify call gubidonius/wellfound-markets --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gubidonius/wellfound-markets"
        }
    }
}

```

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/yE4IeFDu1a5Yg1crP/builds/4YNjv2Jp2D8Lnt5Y6/openapi.json