Airtable Scraper

Extract template galleries, use case showcases, and universe base data from Airtable for workflow automation research. Built on spider-browser .

Get started Docs

target
airtable.com: success rate
99.9%: latency
~4ms

Quick start

Extract data in minutes.

airtable-scraper.ts

import { SpiderBrowser } from "spider-browser";

const spider = new SpiderBrowser({
  apiKey: process.env.SPIDER_API_KEY!,
  stealth: 2,
});

await spider.connect();
const page = spider.page!;
await page.goto("https://www.airtable.com/templates");
await page.content(10000);

const data = await page.extractFields({
  title: "h1",
  description: "[data-testid='template-description']",
  category: "[data-testid='template-category']",
  creator: "[data-testid='template-creator']",
  uses: "[data-testid='template-uses']",
  fields: "[data-testid='template-fields']",
});

console.log(data);
await spider.close();

ready to run · spider-browser · TypeScript

Fetch API

One endpoint for airtable.com.

Structured JSON from airtable.com with a single POST. AI-resolved selectors, cached on the first call.

POST /fetch/airtable.com/

Template nameCategoryDescriptionCreatorViews countFields

Try it Fetch docs

cURL

curl -X POST https://api.spider.cloud/fetch/airtable.com/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"return_format": "json"}'

Python

import requests

resp = requests.post(
    "https://api.spider.cloud/fetch/airtable.com/",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={"return_format": "json"},
)
print(resp.json())

Node.js

const resp = await fetch("https://api.spider.cloud/fetch/airtable.com/", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ return_format: "json" }),
});
const data = await resp.json();
console.log(data);

Extraction