AI Web Scraper API for Structured Web Data

Describe the data you need in plain English. ScrapingBee renders JavaScript pages, handles the scraping infrastructure, and uses AI to extract the data you need, including structured JSON.

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A prompt asking to scrape camera models and the structured JSON output
Mike Ritchie

Mike Ritchie

CEO @ SeekWell

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ScrapingBee simplified our day-to-day marketing and engineering operations a lot. We no longer have to worry about managing our own fleet of headless browsers, and we no longer have to spend days sourcing the right proxy provider

AI clients and a browser connected to ScrapingBee

What Is AI Web Scraping?

AI web scraping is the use of artificial intelligence to identify and extract useful information from web pages without relying entirely on fixed CSS selectors or custom parsing rules. An AI scraper can interpret page content, understand natural-language extraction instructions, and return relevant data in a structured format. This makes AI-powered web scraping especially useful for complex, unstructured, or frequently changing websites.

How it works

How ScrapingBee's AI Web Scraper Works

1

Get your API key

Create a ScrapingBee account and use your API key to authenticate requests to the Web Scraping API.

Creating a ScrapingBee account and copying the API key
2

Describe the data you need

Provide the target URL and explain what you want to extract in plain English with ai_query, or define specific fields and data types with ai_extract_rules.

A chat prompt describing the data to extract
3

Send the scraping request

ScrapingBee loads the target page, renders JavaScript when needed, and passes the page content to the AI extraction layer to identify the information that matches your instructions.

A request sent to the ScrapingBee API
4

Receive the extracted data

Get the result directly in the API response. Use free-form AI extraction for natural-language answers or extraction rules when you need predictable, structured JSON for your application or data pipeline.

Extracted data returned as JSON

Dev-friendly control

AI Extraction Parameters

ai_query

Natural-language query

Describe the information you want to extract from the page in plain English.

ai_extract_rules

Extraction rules

Define the fields you want to extract using JSON rules with natural-language descriptions. ScrapingBee returns the matching data as structured JSON.

ai_selector

AI selector

Optionally provide a CSS selector to limit AI extraction to a specific part of the page, improving precision and reducing processing time.

See it in action

Extract Web Data with AI

See how ScrapingBee turns natural-language instructions or extraction rules into structured web data. Try the examples with cURL, Python, JavaScript, or the ScrapingBee CLI and compare each request with its actual response.

Request

curl -G "https://app.scrapingbee.com/api/v1" \
  -H "Authorization: Bearer YOUR-API-KEY" \
  --data-urlencode "url=https://www.scrapingbee.com/blog/" \
  --data-urlencode 'ai_extract_rules={
    "title": "title of the blog post",
    "summary": "a 5 sentences summary of the blog post"
  }' \
  --data-urlencode "ai_selector=#content" \
  --data-urlencode "render_js=true"

Response

200 OK
{
  "title": "How to web scrape with ScrapingBee",
  "summary": "We help you get better at web-scraping: detailed tutorial, case studies and writing by industry experts"
}

Features

Why Use an AI-Powered Web Scraper?

AI-powered web scraping combines traditional scraping infrastructure with AI-based extraction, making it easier to collect structured data from complex and unstructured web pages.

Reduce selector maintenance

Describe the data you need in natural language instead of building and maintaining CSS or XPath selectors for every field.

Extract unstructured data

Use an AI scraper to identify useful information even when the source page does not provide a clean, predictable structure.

Handle layout changes more easily

AI-based extraction relies less on exact element locations, making scraping workflows less brittle when page layouts change.

Return structured JSON

Define the fields and data types you need and receive structured results ready for applications, databases, or data pipelines.

Scrape JavaScript-powered websites

ScrapingBee can render JavaScript before AI extraction, allowing data to be collected from dynamic pages and single-page applications.

Manage proxies and difficult requests

Use ScrapingBee's proxy infrastructure, including premium and stealth proxy options, without maintaining your own proxy pool.

Scale AI web scraping through an API

Run the same extraction workflow across many URLs without managing your own browsers, proxy rotation, or scraping infrastructure.

Agents + Remote MCP

Give ChatGPT and AI Agents Live Web Data

Connect ChatGPT, Claude, Cursor, or another MCP-compatible client to ScrapingBee and give your AI agents access to live web data whenever they need it.

Page text & Markdown

Read clean page content for conversations, research, RAG, and other LLM workflows.

HTML

Retrieve the page source when your agent needs the underlying markup.

Structured data

Extract specific fields from web pages and return them in a structured format.

Screenshots

Capture rendered pages for visual analysis and workflows that need more than text.

Web search

Search the web and let your agent discover pages before scraping them.

AI clients connected to ScrapingBee's Remote MCP server and a scraped page
ScrapingBee hosts the Remote MCP server, so you don't need to run a ScrapingBee server locally. Connect your MCP client, authenticate with your API key, and let the agent call the available scraping tools when needed.

Use cases

AI Web Scraping Use Cases

Use AI-powered web scraping to turn changing, unstructured web pages into data your applications and workflows can use.

Product and price monitoring

Extract product names, prices, availability, ratings, and other attributes across ecommerce pages.

Input

Product page URLs

Output

Structured product and pricing data

Market and news research

Collect relevant facts, announcements, article metadata, and other public information from multiple web sources.

Input

News and company pages

Output

Titles, dates, summaries, and source data

Public lead enrichment

Enrich existing business records with publicly available company information from websites and directories.

Input

Company URLs

Output

Industry, location, description, and contact details when publicly available

Job data collection

Extract job titles, locations, requirements, salaries, and other details from public job listings.

Input

Job listing pages

Output

Structured job records

RAG and LLM pipelines

Convert web pages into clean text or Markdown for retrieval, indexing, knowledge bases, and other AI workflows.

Input

Documentation or content URLs

Output

LLM-ready text or Markdown

AI training datasets

Collect and structure publicly available web data for permitted AI and machine learning datasets while respecting applicable laws, website terms, and data rights.

Input

Approved public web sources

Output

Structured dataset records

AI Web Scraping vs. Traditional Scraping

FeatureAI web scrapingTraditional web scraping
SetupDescribe the data you need in natural language or define an extraction schemaWrite parsing logic and selectors for the target page
SelectorsCan reduce or avoid field-specific CSS and XPath selectorsTypically relies on CSS selectors, XPath, or custom HTML parsing
Page changesMore tolerant of layout changes when the underlying content remains similarSelector-based extraction may require updates when the DOM structure changes
Unstructured contentWell suited to identifying and extracting information from varied or loosely structured pagesWorks best when the required data appears in predictable locations
OutputCan return requested fields as structured JSON or natural-language resultsReturns whatever structure is defined by your parsing code
ValidationAI-extracted fields should be validated when accuracy is importantDeterministic parsing can provide highly predictable results when selectors remain valid
Best fitChanging websites, heterogeneous pages, rapid extraction setup, and unstructured dataStable page structures, highly deterministic workflows, and performance-sensitive extraction

Reliable Data Extraction from Dynamic Websites

AI extraction still depends on getting the right page content first. ScrapingBee handles browser rendering and proxy infrastructure before the data is passed to the extraction layer.

JavaScript rendering

Render dynamic pages in a headless browser before extraction. This helps with websites and single-page applications where important content is loaded by JavaScript.

Wait for the right content

Use fixed waits, browser events, or CSS/XPath conditions to delay extraction until the content you need has appeared on the page.

Managed browser infrastructure

Run browser-based scraping without maintaining your own headless browser fleet. ScrapingBee handles the browser infrastructure behind each request.

Premium and stealth proxies

Use premium proxy pools for difficult websites or stealth proxies for harder targets when the standard configuration is not enough.

AI Web Scraping API Pricing

Cancel anytime, no questions asked!

API Credits
Concurrent requests
JavaScript rendering
Rotating & Premium Proxies
Geotargeting
Screenshots, Extraction Rules, Google Search API
Dedicated Scraping APIs
Priority Email Support
Dedicated Account Manager
Team Management
Hobby $19/mo
75,000
25
-
-
-
Freelance $49/mo
250,000
50
-
-
-
Business $249/mo
3,000,000
200
Business + $599/mo
8,000,000
400
All prices are exclusive of VAT.

Scale your AI extraction workload

Talk to our team about high-volume AI extraction, custom credit requirements, and concurrent workloads.
Talk to a product expert

Test AI extraction on your own pages

Try the AI Web Scraper API with 1,000 free credits and test ai_query and ai_extract_rules on your own pages.
Start for free No credit card required.

AI extraction cost

Requests using ai_query or ai_extract_rules consume 5 additional credits on top of the regular API request cost. The base request cost still depends on options such as JavaScript rendering and proxy type.

Frequently Asked Questions

What is AI web scraping?
AI web scraping is a method of using artificial intelligence to understand web page content and extract relevant information based on natural-language instructions or a defined schema. Unlike traditional scraping, an AI web scraper can reduce the need to write and maintain selectors for every field, which is useful for unstructured or frequently changing pages.
How is an AI web scraper different from a traditional web scraper?
An AI web scraper differs from a traditional web scraper by using AI to identify data based on meaning and extraction instructions, rather than relying primarily on fixed CSS selectors, XPath expressions, or custom parsing logic. This can reduce selector maintenance and make extraction more tolerant of layout changes, although important fields should still be validated.
Can I extract structured data without writing CSS or XPath selectors?
Yes. ScrapingBee's ai_extract_rules parameter lets you describe the fields you want in natural language and receive structured JSON without writing a CSS or XPath selector for each field. You can also define expected data types such as strings, numbers, and booleans.
Can the AI scraper handle JavaScript-rendered websites?
Yes. ScrapingBee can render JavaScript before running AI extraction, so it can work with dynamic websites where content is loaded after the initial HTML response. You can also wait for specific elements or browser events before extracting the data you need.
What output formats are available?
For AI extraction, you can use ai_query for a natural-language result or ai_extract_rules for structured JSON. ScrapingBee's web scraping API can also return rendered HTML, page source, plain text, and Markdown, as well as capture webpage screenshots for workflows that need visual output.
Can I use the AI web scraper with Python?
Yes. You can use ScrapingBee's Python library to send an ai_query or ai_extract_rules with your scraping request. This makes it possible to add AI web scraping to Python applications, data pipelines, monitoring jobs, and other automated workflows without running your own browser or proxy infrastructure.
Does ScrapingBee provide a CLI for AI web scraping?
Yes. The ScrapingBee CLI supports AI extraction directly from the terminal with --ai-query, --ai-extract-rules, and --ai-selector. You can also use the CLI for crawling websites, processing batches of URLs, JavaScript rendering, Markdown output, screenshots, and other scraping workflows.
Can ChatGPT scrape websites using ScrapingBee?
Yes. You can connect ScrapingBee's hosted Remote MCP server to ChatGPT and give it access to live web scraping and search tools. Once connected, ChatGPT can request page text or HTML, extract data, capture screenshots, and search the web through ScrapingBee when a conversation requires current web data.
What is the difference between the AI Web Scraping API, MCP server, and GPT API?
The AI Web Scraping API extracts information from a URL using natural-language queries or AI extraction rules and is designed for programmatic scraping workflows. The Remote MCP server exposes ScrapingBee tools to AI clients such as ChatGPT, Claude, and Cursor so agents can access live web data during a conversation or task. The GPT API works in the other direction: your application sends a prompt to a GPT model through ScrapingBee and receives an AI-generated response, with optional web search.
Can I use ScrapingBee for RAG or AI training datasets?
Yes. ScrapingBee can return web pages as clean text or Markdown, which can be processed, chunked, indexed, and used in RAG pipelines or knowledge bases. It can also help collect public web data for permitted AI and machine learning datasets, subject to applicable laws, website terms, copyright, privacy requirements, and data usage rights.
How accurate is AI web scraping?
There is no fixed accuracy rate for AI web scraping: accuracy depends on the page structure, content, and extraction instructions. AI extraction can work well with complex or inconsistent layouts, but results are not deterministic and important fields should still be validated against expected types, ranges, or business rules. Using ai_selector to focus extraction on the relevant part of a page can also improve precision and reduce processing time.
How much does AI web scraping cost?
ScrapingBee's ai_query and ai_extract_rules parameters each add 5 credits to the regular cost of the scraping request. The base request cost depends on the other features used, such as JavaScript rendering or proxy options. New ScrapingBee accounts receive 1,000 free API credits to test the service.
Is AI web scraping legal?
AI web scraping is subject to the same legal considerations as other forms of web scraping. Whether a specific use is permitted depends on factors such as the jurisdiction, the website's terms, the type of data collected, copyright and privacy rights, and how the data will be used. Check the relevant website rules and applicable laws before collecting or reusing data, especially personal, copyrighted, or restricted information.

AI Web Scraping Guides and Documentation

Explore practical guides and reference documentation for AI extraction, dynamic websites, LLM workflows, and AI agent integrations.

AI data extraction

Learn how to use ai_query, ai_extract_rules, and ai_selector to extract web data using natural-language instructions and structured schemas.

View AI extraction docs

AI web scraping with Python

Build an AI web scraper in Python and extract structured data without maintaining field-specific CSS or XPath selectors.

Read the Python guide

ScrapingBee CLI

Test AI extraction from your terminal, scrape individual pages, crawl websites, process batches, and prepare data for LLM workflows.

View CLI documentation

Remote MCP

Connect ChatGPT, Claude, Cursor, and other MCP clients to ScrapingBee for live web scraping, search, screenshots, and data extraction.

View Remote MCP documentation

Markdown output

Return the main content of a web page as Markdown for LLM prompts, knowledge bases, RAG pipelines, and other AI workflows.

Learn about Markdown output

JavaScript rendering

Render dynamic and JavaScript-powered websites in a managed browser before extracting the content you need.

View JavaScript rendering documentation

Responsible web scraping

Review practical guidance on rate limits, website rules, data collection practices, and legal and ethical considerations when scraping the web.

Read web scraping best practices

Ready to start AI web scraping?

Get 1,000 free API credits to test AI extraction, JavaScript rendering, and other ScrapingBee features.

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