PyScrappy
Enables AI agents to reliably extract and structure web data without manual parsing, reducing time spent on data preparation and improving data quality for a…
Python web scraping toolkit and MCP server that gives AI agents clean, structured web data from any URL or built-in scrapers.
- Extract product prices and specifications from competitor websites for market analysis
- Gather structured data from news sites to feed into analytics dashboards automatically
- Collect customer reviews and ratings from multiple sources into unified datasets
Enables AI agents to reliably extract and structure web data without manual parsing, reducing time spent on data preparation and improving data quality for analytics pipelines.
Data engineering teams building AI-powered analytics systems that require automated web data collection and normalization.
https://github.com/mldsveda/PyScrappy
By mldsveda
How to Get It
claude plugins install mldsveda/PyScrappy
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me extract product prices and specifications from competitor websites for market analysis
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 106 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 106 GitHub stars; contributors unknown; last commit 0d ago; license MIT.