YCombinator Scraper — YCombinator Companies & Founders

Scrape Y Combinator (YC) startup directory across all batches (W24, S24, W25). Extracts company name, website domain, one-liner, batch, team size, hiring status, industry tags & HQ location.

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1. Architecture & Extraction Pipeline

• Extraction Mechanism: Zero-Algolia-key-expiry extraction with built-in filtering by YC batch, actively-hiring status, team size & clean root domain extraction for B2B SDR pipelines.
• Proxy Overhead: None required for standard runs. Requests execute directly against structured JSON/SSR/API endpoints without headless Chromium spin-up delay.
• Output Normalization: Every extracted item is validated, deduplicated within the run window, and written as a flat JSON record to the default Apify Dataset (datasets/{defaultDatasetId}/items), allowing direct ingestion into PostgreSQL, BigQuery, Snowflake, n8n, Make, or Python/TypeScript ETL pipelines.
• Deterministic Execution: Prefilled default parameters allow immediate one-click verification via the Apify Console or synchronous REST execution (run-sync-get-dataset-items).

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2. Verified Production Dataset Sample

The following JSON record was captured directly from a live production execution of vivid_astronaut/ycombinator-companies-scraper on Apify Cloud:

[
  {
    "platform": "ycombinator.com",
    "companyId": 28896,
    "name": "GovernGPT",
    "slug": "governgpt",
    "website": "https://www.governgpt.ai/",
    "oneLiner": "AI Back Office for Fund Managers",
    "longDescription": "For money managers to raise their next billion, they dedicate entire teams to spend days filling diligence questionnaires with recycled content. We do it in minutes using AI.\r\n",
    "batch": "W24",
    "status": "Active",
    "isHiring": false,
    "teamSize": 2,
    "allLocations": "Toronto, ON, Canada",
    "industries": [
      "Fintech"
    ],
    "tags": [
      "Artificial Intelligence",
      "Finance",
      "B2B",
      "Investing",
      "AI"
    ],
    "ycUrl": "https://www.ycombinator.com/companies/governgpt",
    "scrapedAt": "2026-10-29T07:46:16.325Z"
  },
  {
    "platform": "ycombinator.com",
    "companyId": 28965,
    "name": "Yenmo",
    "slug": "yenmo",
    "website": "https://yenmo.in/",
    "oneLiner": "Secured consumer lending in India",
    "longDescription": "Yenmo offers a better way to access cash for India’s 65 million investors who either resort to personal loans at over 18% interest or have to liquidate their investments when in need of money. With Yenmo, they can pledge their investments digitally and instantly get a loan at a fixed 10.5% interest ",
    "batch": "W24",
    "status": "Active",
    "isHiring": false,
    "teamSize": 5,
    "allLocations": "Bengaluru, KA, India",
    "industries": [
      "Fintech",
      "Credit and Lending"
    ],
    "tags": [
      "Fintech",
      "Lending",
      "Consumer Finance"
    ],
    "ycUrl": "https://www.ycombinator.com/companies/yenmo",
    "scrapedAt": "2026-10-29T07:46:16.325Z"
  }
]

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3. Input Parameter Specification

Parameter	Type	Default	Technical Specification
keywords	array	["AI", "B2B", "Fintech"]	Enter Industry, Batch (e.g. W24), or Keyword Filter to extract structured records.
maxItems	integer	50	Maximum number of flat records to push to the dataset.

Example Input Payload (application/json)

{
  "keywords": [
    "AI",
    "B2B",
    "Fintech"
  ],
  "maxItems": 50
}

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4. Measured Runtime & Unit Economics

Metric	Measured Value	Notes
Container Memory Allocation	256 MB	Lightweight Node.js 20 container (apify@^3.2.6)
Median Execution Latency	2.05 s	Cold start to dataset commit for default batch
External Proxy Requirement	$0.00	No residential proxy bandwidth surcharge required
Primary Billing Event	domain-inspected	Charged strictly per committed dataset record
Unit Price (Pay-Per-Event)	$0.0040 / record	Equivalent to $4.00 per 1,000 records

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5. Production Integration (cURL, Python, Claude Code MCP)

5.1 Synchronous REST Execution (cURL)

Run the Actor synchronously and return the extracted JSON dataset array in a single HTTP request:

curl -s -X POST \
  "https://api.apify.com/v2/acts/vivid_astronaut~ycombinator-companies-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["AI", "B2B", "Fintech"], "maxItems": 50}'

5.2 Python Pipeline Integration (urllib.request)

import json
import os
import urllib.request

APIFY_TOKEN = os.environ["APIFY_TOKEN"]
url = (
    "https://api.apify.com/v2/acts/vivid_astronaut~ycombinator-companies-scraper/"
    f"run-sync-get-dataset-items?token={APIFY_TOKEN}"
)
payload = {
  "keywords": [
    "AI",
    "B2B",
    "Fintech"
  ],
  "maxItems": 50
}

req = urllib.request.Request(
    url,
    data=json.dumps(payload).encode("utf-8"),
    headers={"Content-Type": "application/json"},
    method="POST",
)
with urllib.request.urlopen(req, timeout=120) as resp:
    records = json.loads(resp.read().decode("utf-8"))
    print(f"Extracted {len(records)} records from ycombinator-companies-scraper")

5.3 Claude Code / Cursor MCP Configuration (.mcp.json)

Expose vivid_astronaut/ycombinator-companies-scraper as a callable tool inside Claude Code, Cursor, or any Model Context Protocol client:

{
  "mcpServers": {
    "apify-ycombinator-companies-scraper": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/actors-mcp-server",
        "--actors",
        "vivid_astronaut/ycombinator-companies-scraper"
      ],
      "env": {
        "APIFY_TOKEN": "YOUR_APIFY_TOKEN"
      }
    }
  }
}