ChatGPT Scraper

Collect ChatGPT answers through the Scrapeless LLM Chat Scraper API, including Markdown responses, search links, source references, shopping products, and ads, without reverse-engineering the ChatGPT UI, maintaining browsers, or building your own anti-blocking stack.

Use this repo when you need a repeatable way to monitor ChatGPT answers for GEO and AI search visibility, compare prompts across regions, audit cited sources, track shopping recommendations, or pipe AI responses into analytics and automation workflows.

• Full documentation: https://docs.scrapeless.com/en/llm-chat-scraper/quickstart/introduction/
• Get your x-api-token: https://app.scrapeless.com/passport/login?redirect=/quick-start
• API endpoint: POST https://api.scrapeless.com/api/v2/scraper/execute

How it works

Send a single POST request to the Scrapeless endpoint with your API token in the x-api-token header. The body specifies the actor (scraper.chatgpt) and an input object with your prompt and options. The API runs the query and returns the structured result in task_result.

POST https://api.scrapeless.com/api/v2/scraper/execute
Content-Type: application/json
x-api-token: <YOUR_API_TOKEN>

Quick start (curl)

curl 'https://api.scrapeless.com/api/v2/scraper/execute' \
  --header 'Content-Type: application/json' \
  --header 'x-api-token: YOUR_API_TOKEN' \
  --data '{
    "actor": "scraper.chatgpt",
    "input": {
      "prompt": "Most reliable proxy service for data extraction",
      "country": "US",
      "web_search": true,
      "shopping": false
    }
  }'

To receive the result asynchronously, add a webhook object:

"webhook": { "url": "https://www.your-webhook.com" }

Request parameters

The request body has three top-level fields: actor (always scraper.chatgpt), input (below), and an optional webhook.

Parameter (input.*)	Type	Required	Description
prompt	string	Yes	Prompt to send to ChatGPT.
country	string	Yes	Country / region code (e.g. US, JP).
web_search	boolean	No	Enable web search enrichment.
shopping	boolean	No	Fetch shopping data. Defaults to true. When enabled, product info is returned in products.

Billing note: When the response includes shopping data (the products field), the call is charged at 2× the base rate due to the extra work of extracting product information from multiple sources.

Response

A successful call returns a status envelope; the scraped data lives in task_result:

{
  "status": "success",
  "task_id": "e705743d-da2e-4163-9ccd-eef62529ff72",
  "task_result": {
    "prompt": "Most reliable proxy service for data extraction",
    "result_text": "...markdown answer...",
    "model": "gpt-5-1",
    "web_search": true,
    "links": [],
    "search_result": [
      { "attribution": "example.com", "title": "...", "snippet": "...", "url": "https://..." }
    ],
    "content_references": [],
    "products": [],
    "ads": {},
    "map": {}
  }
}

Top-level fields

Field	Type	Description
status	string	Request status, e.g. success.
task_id	string	Unique identifier for the task.
task_result	object	Scraped result (fields below).

task_result fields

Field	Type	Description
prompt	string	Original prompt.
result_text	string	Markdown response from ChatGPT.
model	string	Model identifier, e.g. gpt-5-1.
web_search	bool	Whether search enrichment ran.
links	array	Supplementary links.
search_result	array	SERP results (attribution, snippet, title, url).
content_references	array	References inside the answer (attribution, title, url).
products	array	Product information (present when shopping is enabled).
ads	object	Ads information returned by ChatGPT.
map	object	Map information returned by ChatGPT.

For the complete field list (product offers, ratings, ad cards, carousels, etc.), see the official documentation.

Code examples

Ready-to-run examples live in examples/:

Language	File	Run
Python	example.py	pip install requests && python example.py
Node.js	example.js	node example.js (Node 18+)
Go	example.go	go run example.go
Java	Example.java	java Example.java (Java 11+)
PHP	example.php	php example.php

All examples read the token from the SCRAPELESS_API_TOKEN environment variable:

export SCRAPELESS_API_TOKEN="your_api_token"

Practical use cases

AI answer monitoring

Track how ChatGPT responds to your brand, product category, documentation topics, or competitor prompts. Store the Markdown answer, search results, and references so your team can measure AI visibility over time.

GEO and SEO research

Run the same prompt across countries to compare which sources ChatGPT cites, how recommendations change by region, and where your content appears in AI-generated answers.

Competitor intelligence

Collect structured ChatGPT answers for competitor names, feature comparisons, pricing questions, and "best tool for..." prompts. Use the output to identify messaging gaps and content opportunities.

Dataset and workflow automation

Pipe ChatGPT answers into internal dashboards, knowledge-base QA systems, spreadsheets, data warehouses, or alerting workflows through the synchronous API response or webhook callback.

Why use Scrapeless for ChatGPT scraping?

Benefit	What it means for your team
One unified API	Query ChatGPT through the same Scrapeless LLM Chat Scraper workflow used for other AI answer engines.
Structured output	Receive Markdown answers, search results, references, products, ads, and prompts in a developer-friendly response.
Less maintenance	Avoid building browser automation, UI selectors, proxy rotation, retries, and anti-blocking logic yourself.
Region-aware analysis	Use country inputs to compare localized AI answers and source citations.
Production integration	Use API tokens, webhooks, and language examples to connect ChatGPT data to real applications quickly.

FAQ

What is ChatGPT Scraper?

ChatGPT Scraper is a Scrapeless LLM Chat Scraper actor that sends prompts to ChatGPT and returns structured answer data, including the Markdown response, search results, content references, shopping products, ads, and map data.

Do I need to run a browser or proxy pool?

No. This repo shows how to call the Scrapeless API. Scrapeless handles the scraping workflow behind the API, so your application only needs to send requests and process the returned data.

What do web_search and shopping do, and how are they billed?

web_search enables web search enrichment so the answer includes SERP-style search_result data. shopping fetches product information into the products field. When the response includes shopping data, the call is charged at 2× the base rate due to the extra work of extracting product information from multiple sources.

Can I get results asynchronously?

Yes. Add a webhook object with your callback URL to receive results asynchronously when the task completes.

Is this suitable for AI search visibility monitoring?

Yes. The response includes AI-generated Markdown, search results, outbound links, and content references, which makes it useful for GEO analysis, brand monitoring, source tracking, and competitive research.

What should I consider before using AI scraping in production?

Make sure your use case complies with applicable laws, platform terms, privacy requirements, and your organization's data policies. Avoid collecting sensitive, private, or unauthorized information.

Learn more

• Scrapeless LLM Chat Scraper documentation
• Supported LLM Chat Scraper actors
• Scrapeless dashboard
• Scrapeless website

Contact us

Need help building a ChatGPT monitoring workflow or scaling AI answer collection?

• Join our Discord.
• Contact us on Telegram.
• For repo-specific issues or improvements, open an issue or pull request in this repository.