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Cursor is an AI-powered code editor built on VS Code. Combined with ScrapeGraphAI, you can write, debug, and iterate on scraping pipelines faster using Cursor’s inline AI assistance. The fastest way to use ScrapeGraphAI in Cursor is via the MCP Server. This lets Cursor’s AI agent call ScrapeGraphAI tools directly without writing any code. See the MCP Server setup for Cursor guide for full instructions.

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Manual integration

If you prefer to write code directly, use the Python or JavaScript SDK.

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Python

Install the SDK: 
pip install scrapegraph-py
Ask Cursor to write a scraping script using Cmd+K or open the chat with Cmd+L:
Write a Python function using scrapegraph_py that extracts the title, author, and date from any blog post URL.
Cursor will generate: 
from scrapegraph_py import Client

def extract_blog_post(url: str) -> dict:
    client = Client(api_key="your-api-key")
    return client.smartscraper(
        website_url=url,
        user_prompt="Extract the title, author name, and publication date",
    )

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JavaScript

Install the SDK: 
npm install scrapegraph-js
Ask Cursor:
Write a JavaScript function using scrapegraph-js that extracts product details from an e-commerce page. 
import { smartScraper } from "scrapegraph-js";

async function extractProduct(url) {
  return await smartScraper(
    "your-api-key",
    url,
    "Extract the product name, price, and availability"
  );
}

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Tips for using Cursor with ScrapeGraphAI

  • Paste error messages into the Cursor chat to get instant fix suggestions.
  • Ask Cursor to add output schemas (output_schema with Pydantic or Zod) to get strongly-typed results.
  • Use @docs in Cursor chat to reference the ScrapeGraphAI docs directly while coding.
Store your API key in a .env file and load it via python-dotenv or process.env — never hardcode it in your source files.