Wellfound Jobs Scraper

Export public startup job listings into a structured dataset for recruiting research, talent-market tracking, and job discovery. This Wellfound Jobs Scraper accepts a role, optional location, or specific public company job pages and returns deduplicated job records with source-page provenance.

It is also a practical Wellfound scraper for recurring job-market workflows: schedule a search, export results to a spreadsheet, or call it from your application. The Actor only handles public job-listing information; it does not apply to jobs, access candidate profiles, or require a personal session.

What you get

Each dataset row is a public job listing. The output is useful for an Angel.co jobs scraper migration or a startup jobs scraper workflow because it includes both normalized job values and the page/search URL that produced them.

{
  "source": "wellfound",
  "searchUrl": "https://wellfound.com/role/r/software-engineer",
  "jobUrl": "https://wellfound.com/jobs/example",
  "jobId": "example",
  "title": "Software Engineer",
  "companyName": "Example Startup",
  "location": "New York, NY",
  "remote": true,
  "salary": "$120k–$160k",
  "page": 1,
  "scrapedAt": "2026-08-29T00:00:00.000Z"
}

Input settings

Who is it for?

• Recruiters and sourcers building a public startup hiring watchlist.
• Talent-market analysts comparing roles, compensation, remote availability, and company demand.
• Job boards and product teams collecting public listings for a research or matching workflow.
• Automation builders who need a repeatable, target-bound public job dataset rather than a manual export.

Pagination, limits, and partial output

Results are saved progressively and deduplicated by public job ID. The Actor follows pages until it reaches maxItems, no new jobs are available, a page repeats, or the shared time budget reaches its persistence reserve.

A completed run can contain fewer than maxItems when the requested public target has fewer results. If the source serves a challenge or a request fails after some rows were saved, the saved rows remain available and RUN-SUMMARY records the outcome and warnings.

API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/wellfound-jobs-scraper').call({
  role: 'software-engineer',
  maxItems: 20,
  includeDescription: true,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("<APIFY_TOKEN>")
run = client.actor("fetch_cat/wellfound-jobs-scraper").call(run_input={
    "role": "software-engineer", "maxItems": 20, "includeDescription": True
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

cURL

curl -X POST "https://api.apify.com/v2/acts/fetch_cat~wellfound-jobs-scraper/runs?token=$APIFY_TOKEN" \
  -H 'content-type: application/json' \
  -d '{"role":"software-engineer","maxItems":20,"includeDescription":true}'

MCP and AI-agent usage

Add this Actor to the Apify MCP Server to let an MCP-compatible client run a public Wellfound job search with structured input and dataset output.

claude mcp add apify -- npx -y @apify/mcp-server --tools fetch_cat/wellfound-jobs-scraper

Or add the server to an MCP configuration:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": ["-y", "@apify/mcp-server", "--tools", "fetch_cat/wellfound-jobs-scraper"],
      "env": { "APIFY_TOKEN": "<APIFY_TOKEN>" }
    }
  }
}

Example prompts: “Find 20 remote software-engineer jobs on Wellfound” or “Export jobs from this public Wellfound company URL.” Start with a small result limit and provide a role, location, or explicit public company URL.

Support

For help, open an issue from the Actor page and include your input (without secrets), approximate run time, and the RUN-SUMMARY value when available.