CourtListener Scraper

Extract court opinions, oral arguments, docket entries, and judge information from CourtListener. Built on spider-browser .

Get started Docs

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

Quick start

Extract data in minutes.

courtlistener-scraper.ts

import { SpiderBrowser } from "spider-browser";

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

await spider.connect();
const page = spider.page!;
await page.goto("https://www.courtlistener.com/?q=artificial+intelligence&type=o&order_by=score+desc");
await page.content();

const data = await page.extractFields({
  title: ".result .result-title a",
  court: ".result .court",
  date: ".result .date-filed",
  snippet: ".result .snippet",
});

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

ready to run · spider-browser · TypeScript

Fetch API

One endpoint for courtlistener.com.

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

POST /fetch/courtlistener.com/

Case nameCourtDate filedDocket numberJudgeStatus

Try it Fetch docs

cURL

curl -X POST https://api.spider.cloud/fetch/courtlistener.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/courtlistener.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/courtlistener.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