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webclaw

Skill Data & Analytics Usable

Fast, local-first web content extraction for LLMs. Scrape, crawl, extract structured data — all from Rust. CLI, REST API, and MCP server.

1,285 starsAGPL-3.0 (check with legal)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Extracts structured data from web pages at scale without external dependencies or API calls. Runs locally, reducing latency and eliminating third-party service costs.

Teams building LLM pipelines that need to ingest and normalize web content reliably without relying on cloud extraction services.

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https://github.com/0xMassi/webclaw

By 0xMassi

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install 0xMassi/webclaw

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars1,285Last updated2026-06-04LicenseAGPL-3.0 (check with legal)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-04 · scanner v1

Community Pulse Active

Discussed on Hacker News, Reddit

25 mentions across 2 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 1,285 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.

Things to check

  • License (AGPL-3.0) may restrict commercial use. Check with your legal team.

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

Ease of Use
2/5
Versatility
4/5
Reliability
3/5
Security
3/5
Overall score2.90 / 5.00 UsableEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 1,285 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.

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