Setup guide
Hermes Agent with Scrapling setup
Set up a Hermes Agent workflow that can run scraping jobs, collect structured data, and keep the process available on a local machine or server.
What this setup is for
Use this when you want an agent-assisted scraping workflow for research, lead collection, competitor monitoring, price tracking, listing checks, or custom website data collection.
- Scrapling handles modern scraping and crawling tasks.
- A server or always-on machine keeps the workflow available.
- The workflow should be scoped to exact websites, target fields, and output format.
Hermes Agent runs the workflow.Install Scrapling
Install Python first, then add Scrapling inside the same environment where your agent workflow will run.
pip install scraplingConnect it to the agent
Create the scraping task, define target URLs and selectors, choose CSV or JSON output, then connect the command to the Hermes workflow trigger.
- Create a small test target first.
- Confirm the output fields are correct.
- Add logging before scheduling recurring runs.
- Keep credentials and proxy details outside project files.
Business-data safety checks
Before collecting data at scale, check target website terms, local rules, rate limits, and the quality of the data you are storing.
- Start with small batches.
- Avoid scraping private or restricted pages.
- Keep raw output separate from CRM-ready output.
- Review failures before increasing volume.
Final checklist
- The installation command or dashboard opens correctly.
- You tested with a small, low-risk workflow first.
- Credentials and business data are not stored in public files.
- You know how to stop, restart, and inspect logs for the workflow.
