- ASYNC
- STATUS
- DATA
- HUMAN
Short answer
How can I run massive scraping jobs without my AI hanging?
Your agent uses ScraperAPI to start asynchronous jobs that run on external infrastructure. You can check the status of these jobs whenever you're ready to process the results. This keeps your conversation fluid while the data is being pulled.
The results.
Where your data lands.
The AI manages the lifecycle of every scraping request.
ASYNC
Background execution
The AI triggers a job that runs independently. You don't have to wait for the page to load to keep talking to your agent.
STATUS
Progress tracking
Your agent checks the job status periodically. It knows exactly when the data is ready for you to use.
DATA
Clean extraction
Once the job finishes, the AI pulls the raw content. You get the specific information you asked for without the noise.
HUMAN
Manual review
The AI hands off the final data to you. You decide if the scraped content meets your needs or if you need to adjust the parameters.
The workflow
What your AI does when a scrape is requested.
The AI handles the handoff between your prompt and the ScraperAPI infrastructure.
Start the job
Your agent sends the target URL and scraping parameters to the API. This starts a process that doesn't block your current chat session.
create_async_jobMonitor progress
The AI periodically asks the API if the specific task is finished. It waits for a successful completion signal.
get_async_jobRetrieve results
Once the status shows as completed, the AI fetches the scraped content. It prepares the data for your next question.
get_async_jobAnalyze data
The AI reads the returned HTML or JSON. It extracts the specific fields you need for your project.
get_async_job
Try it
Copy these to start.
Use these prompts to kick off your first background scraping tasks.
Starting points
Swap out the URLs and target websites with the ones you actually need to scrape.
ScraperAPI Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_nELcO4Myrx7IrBymIKoaUd3mXQyjfxnY1APMhbc3/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — ScraperAPI capabilities are ready to use.
{
"mcpServers": {
"scraperapi-mcp": {
"url": "https://edge.vinkius.com/vk_preview_nELcO4Myrx7IrBymIKoaUd3mXQyjfxnY1APMhbc3/mcp"
}
}
}Start an async scraping job for https://example.com/products to get all product names and prices.
Check the status of my last ScraperAPI job to see if the data is ready.
Run a background scrape on the Amazon search results for 'mechanical keyboards' and tell me when it's done.
Get the results from my completed ScraperAPI job and summarize the top 5 items found.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect ScraperAPI once, then ask.
Just link your account once. Your credentials stay encrypted, and you can start running jobs immediately.
Connect ScraperAPI to your AIFAQ
How the scraping automation behaves
- 01
Will my AI stop responding while the scrape is running?
No. Because the AI uses asynchronous jobs, it sends the request and then stays available for your other questions.
- 02
Can the AI change my ScraperAPI account settings?
No. The AI can only create and check the status of scraping jobs.
- 03
How does the AI know when the data is ready?
The AI uses the job status tool to check if the background task has moved from running to completed.
- 04
Can the AI delete old scraping jobs from my account?
No. The AI only has the ability to create new jobs and retrieve data from existing ones.
- 05
What happens if a scrape fails?
The AI will see the failed status when it checks the job. It will then report the error to you so you can decide how to proceed.
More questions about ScraperAPI? See everything the ScraperAPI Connector can do
Connect ScraperAPI to Claude, Cursor, ChatGPT & more
