Web unlocker use cases

Web Unlocker is a scraping API — you send a URL, it returns the fully rendered HTML. This page shows the most common ways to put that to use.

Scrape a page yourself

The simplest use case: you need the content of a webpage that blocks regular HTTP requests.

Python

import requests

response = requests.get(
    "https://parsing.webunlocker.gologin.com/v1/scrape",
    params={"url": "https://example.com/product/123"},
    headers={"apikey": "YOUR_API_KEY"}
)

html = response.text
print(html)

JavaScript

const html = await fetch(
  "https://parsing.webunlocker.gologin.com/v1/scrape?url=" +
    encodeURIComponent("https://example.com/product/123"),
  { headers: { apikey: "YOUR_API_KEY" } }
).then((r) => r.text());

console.log(html);

No browser to launch, no proxy to configure, no Cloudflare to fight. One call, you get the page. Good for:

Checking prices on a competitor’s site
Pulling job listings, reviews, or product data
Monitoring pages for changes
One-off data collection scripts

Feed content into an AI

Web Unlocker returns raw HTML. Pass that into an LLM to extract structured data, summarize content, or answer questions about the page — no parsing logic needed.

Python + OpenAI

import requests
from openai import OpenAI

html = requests.get(
    "https://parsing.webunlocker.gologin.com/v1/scrape",
    params={"url": "https://news.ycombinator.com"},
    headers={"apikey": "YOUR_API_KEY"}
).text

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {
            "role": "user",
            "content": f"Extract the top 5 story titles and their URLs from this HTML:\n\n{html[:8000]}"
        }
    ]
)

print(response.choices[0].message.content)

JavaScript + Anthropic

import Anthropic from "@anthropic-ai/sdk";

const html = await fetch(
  "https://parsing.webunlocker.gologin.com/v1/scrape?url=" +
    encodeURIComponent("https://news.ycombinator.com"),
  { headers: { apikey: "YOUR_API_KEY" } }
).then((r) => r.text());

const client = new Anthropic();
const message = await client.messages.create({
  model: "claude-opus-4-5",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: `Extract the top 5 story titles and their URLs from this HTML:\n\n${html.slice(0, 8000)}`,
    },
  ],
});

console.log(message.content[0].text);

Good for:

Extracting structured data (prices, names, dates) without writing parsers
Summarizing articles or product pages
Comparing multiple pages and drawing conclusions
Building research or monitoring tools powered by AI

Use it inside an AI agent

Give your AI agent a scrape tool backed by Web Unlocker. The agent can then browse the web on its own — fetching pages, reading content, and taking action — without you writing any browsing logic.

import requests
import anthropic

def scrape(url: str) -> str:
    """Fetch a URL and return its rendered HTML."""
    return requests.get(
        "https://parsing.webunlocker.gologin.com/v1/scrape",
        params={"url": url},
        headers={"apikey": "YOUR_API_KEY"}
    ).text

tools = [
    {
        "name": "scrape",
        "description": "Fetch the rendered HTML of any URL, including JavaScript-heavy and protected sites.",
        "input_schema": {
            "type": "object",
            "properties": {
                "url": {"type": "string", "description": "The URL to scrape"}
            },
            "required": ["url"]
        }
    }
]

client = anthropic.Anthropic()
messages = [
    {"role": "user", "content": "What is the current price of the iPhone 16 Pro on apple.com?"}
]

while True:
    response = client.messages.create(
        model="claude-opus-4-5",
        max_tokens=1024,
        tools=tools,
        messages=messages
    )

    if response.stop_reason == "end_turn":
        print(response.content[0].text)
        break

    tool_results = []
    for block in response.content:
        if block.type == "tool_use" and block.name == "scrape":
            html = scrape(block.input["url"])
            tool_results.append({
                "type": "tool_result",
                "tool_use_id": block.id,
                "content": html[:10000]
            })

    messages.append({"role": "assistant", "content": response.content})
    messages.append({"role": "user", "content": tool_results})

The agent decides when to scrape and what URL to fetch. Web Unlocker handles the actual retrieval. Good for:

Research agents that browse the web autonomously
Price comparison or deal-finding bots
Competitive intelligence pipelines
Any agent that needs real-time web data

Scrape many pages at once

Run requests concurrently to collect data from multiple URLs in parallel.

import requests
from concurrent.futures import ThreadPoolExecutor

API_URL = "https://parsing.webunlocker.gologin.com/v1/scrape"
API_KEY = "YOUR_API_KEY"

urls = [
    "https://example.com/page/1",
    "https://example.com/page/2",
    "https://example.com/page/3",
]

def scrape(url):
    response = requests.get(
        API_URL,
        params={"url": url},
        headers={"apikey": API_KEY}
    )
    return url, response.text

with ThreadPoolExecutor(max_workers=5) as executor:
    results = list(executor.map(scrape, urls))

for url, html in results:
    print(f"{url}: {len(html)} chars")

Good for:

Scraping entire product catalogs or listing pages
Bulk data collection for training datasets
Monitoring many pages simultaneously

Summary

Use case	What you do	What you get
Scrape a single page	GET with URL param	Rendered HTML
Feed into an LLM	Scrape → pass to model	Extracted data or summary
AI agent tool	Agent calls on demand	Real-time web content
Bulk scraping	Concurrent requests	HTML for each URL

Use it from the CLI

Skip writing code entirely — use the Gologin Web Access CLI for common scraping workflows:

npm install -g gologin-web-access
export GOLOGIN_WEB_UNLOCKER_API_KEY="wu_..."

# batch scrape multiple pages
gologin-web-access batch-scrape \
  https://example.com/page/1 \
  https://example.com/page/2 \
  https://example.com/page/3 \
  --format text --only-main-content --summary

# crawl a site
gologin-web-access crawl https://docs.example.com --format markdown --limit 50 --max-depth 2

# monitor page changes
gologin-web-access change-track https://example.com/pricing --format markdown

# extract structured data with a schema
gologin-web-access extract https://example.com/product/123 --schema ./product-schema.json

# search the web
gologin-web-access search "best antidetect browser 2026" --limit 10

See Web Access CLI for the full command reference.

Summary

Use case	What you do	What you get
Scrape a single page	GET with URL param	Rendered HTML
Feed into an LLM	Scrape → pass to model	Extracted data or summary
AI agent tool	Agent calls on demand	Real-time web content
Bulk scraping	Concurrent requests	HTML for each URL
CLI workflows	`gologin-web-access` commands	Text, markdown, JSON, batch results

See Quickstart to make your first request.

Introduction

API Reference

Scraping API & Web Unlocker

Node.js SDK

Python SDK

Limitations

Scrape a page yourself

Python

JavaScript

Feed content into an AI

Python + OpenAI

JavaScript + Anthropic

Use it inside an AI agent

Scrape many pages at once

Summary

Use it from the CLI

Summary

Introduction

API Reference

Scraping API & Web Unlocker

Node.js SDK

Python SDK

Limitations

​Scrape a page yourself

​Python

​JavaScript

​Feed content into an AI

​Python + OpenAI

​JavaScript + Anthropic

​Use it inside an AI agent

​Scrape many pages at once

​Summary

​Use it from the CLI

​Summary

Scrape a page yourself

Python

JavaScript

Feed content into an AI

Python + OpenAI

JavaScript + Anthropic

Use it inside an AI agent

Scrape many pages at once

Summary

Use it from the CLI

Summary