- AUTOMATED
- MONITORED
- DELIVERED
- HUMAN
Short answer
How can I start massive scraping jobs using my AI?
You tell your agent which platform and data you need, and it kicks off an asynchronous scraping job. It tracks the progress and hands you the final dataset when it's done.
Data collection outcomes
What you get from your agent
The agent manages the technical execution and delivers these specific results.
AUTOMATED
Active scraping jobs
The agent starts large-scale extractions on sites like Amazon. You don't have to manage individual requests or proxies yourself.
MONITORED
Real-time status updates
Your agent watches the job as it runs. You can ask it for updates to see exactly how much data has been collected.
DELIVERED
Final datasets
When the job finishes, the agent pulls a snapshot of the data. You get a clean file ready for your own analysis.
HUMAN
Manual data review
The agent provides the raw data, but you decide how to use it. You stay in control of the final validation and decision making.
The workflow
What your AI does when the request arrives.
The agent moves from your command to a finished dataset using these steps.
Start the job
The agent translates your request into a scraping instruction for the target platform.
trigger_datasetCheck progress
Because these jobs are asynchronous, the agent checks the status to see if the collection is still running.
get_dataset_progressRetrieve data
Once the job is complete, the agent pulls the final data snapshot for you.
get_dataset_snapshotVerify status
The agent uses status checks to confirm when the data is ready for you to download.
get_dataset_progress
Try it
Copy these to start.
Use these prompts to kick off your first collection.
Starting points
These are opening lines. Swap out the platform and the specific data you want to collect.
Bright Data Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_Z06xKXBLbhmRgabDfSd6BBkkFtoyph9gsiWpikY1/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 — Bright Data capabilities are ready to use.
{
"mcpServers": {
"bright-data-mcp": {
"url": "https://edge.vinkius.com/vk_preview_Z06xKXBLbhmRgabDfSd6BBkkFtoyph9gsiWpikY1/mcp"
}
}
}Start a scraping job on Amazon for all high-rated coffee makers in the US.
Trigger a dataset collection for LinkedIn profiles of software engineers in Berlin.
Check the progress of my current Amazon product scraping job.
Get a snapshot of the latest dataset collected from LinkedIn job postings.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Bright Data once, then ask.
Log in once to link your account. Your credentials stay encrypted, and you can immediately start giving commands to your agent.
Connect Bright Data to your AIFAQ
How this task behaves
- 01
Can my AI scrape any website?
No. The agent can only trigger jobs on platforms supported by the Bright Data tools.
- 02
Does the AI handle proxy rotation?
Yes. The agent triggers the job through Bright Data, which manages the proxy infrastructure automatically.
- 03
Can the AI change my Bright Data account settings?
No. The agent can only trigger jobs, check progress, and get snapshots. It cannot modify your account configuration.
- 04
Will the AI delete my existing datasets?
No. The tools provided only allow for triggering new jobs and retrieving data. There is no tool to delete data.
- 05
How do I know when the data is ready?
You can ask your agent to check the progress of the job at any time.
More questions about Bright Data? The Connector page answers them. See everything the Bright Data Connector can do
Connect Bright Data to Claude, Cursor, ChatGPT & more
