Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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╚═╝ ╚═╝╚═╝ ╚═╝ ╚══╝╚══╝ ╚══════╝╚═════╝ ╚═╝ ╚═╝// it crawls so your agents don't have to
KRWL3R is written in 1337speak, referencing Linkin Park's "KRWLNG" from the Reanimation) album (2002) — where "Crawling" was reimagined without vowels. This project does the same: reimagines web crawling for the AI agent era.
What is KRWL3R
KRWL3R is a web intelligence engine purpose-built for AI agents. It combines two battle-tested open source projects into a unified, agent-friendly interface:
- [Scrapling](https://github.com/D4Vinci/Scrapling) — adaptive scraping with auto-healing selectors that survive website redesigns
- [PinchTab](https://github.com/pinchtab/pinchtab) — headless browser control with intelligent text extraction (~800 tokens per page)
Instead of dumping raw HTML at your LLM, KRWL3R extracts clean, structured, token-efficient content — and exposes it through MCP, HTTP API, CLI, and ACP interfaces so any agent can use it.
Features
| Category | What you get |
|---|---|
| Stealth scraping | Anti-bot evasion, fingerprint rotation, realistic browser profiles |
| Auto-healing selectors | Selectors adapt when sites change layout — no more broken scrapers |
| Dynamic content | Full JavaScript rendering via headless Chrome |
| Token-efficient output | Pages compressed to ~800 tokens with semantic structure preserved |
| Browser control | Click, type, scroll, screenshot — full interaction when scraping isn't enough |
| Multi-instance | Run parallel browser sessions for concurrent extraction |
| MCP server | Native Model Context Protocol — plug into Claude, Cursor, Windsurf, and more |
| HTTP API | REST endpoints for any language or framework |
| CLI | Pipe web data directly into shell workflows |
| ACP support | Agent Communication Protocol for Gemini CLI and other ACP clients |
Quick Start
Install
pip install krwl3rScrape a page
from krwl3r import Scraper
scraper = Scraper()
result = scraper.extract("https://example.com")
print(result.title) # Page title
print(result.content) # Clean text, ~800 tokens
print(result.metadata) # Structured metadataControl a browser
from krwl3r import Browser
async with Browser() as browser:
page = await browser.new_page("https://example.com")
await page.click("button#load-more")
content = await page.extract()
print(content.text)Use with Claude Desktop (MCP)
Add to your claude_desktop_config.json:
{
"mcpServers": {
"krwl3r": {
"command": "krwl3r",
"args": ["mcp"]
}
}
}Then ask Claude: "Scrape the pricing page at example.com and summarize the plans."
Compatibility
KRWL3R works with any AI tool that supports MCP, HTTP, or CLI interfaces.
| Client | Protocol | Status |
|---|---|---|
| Claude Desktop | MCP | Supported |
| Claude Code | MCP | Supported |
| Cursor | MCP | Supported |
| Windsurf | MCP | Supported |
| OpenCode | MCP | Supported |
| Gemini CLI | ACP | Supported |
| Codex CLI | HTTP / CLI | Supported |
| Kimi CLI | HTTP / CLI | Supported |
| Forge | HTTP / MCP | Supported |
| Any HTTP client | REST API | Supported |
Architecture
┌─────────────────────────────┐
│ AI AGENTS │
│ Claude, Gemini, Codex, ... │
└──────────┬──────────────────┘
│
┌─────────────────────┼─────────────────────┐
│ │ │
┌────▼────┐ ┌────▼────┐ ┌────▼────┐
│ MCP │ │ HTTP │ │ ACP │
│ Server │ │ API │ │ Server │
└────┬────┘ └────┬────┘ └────┬────┘
│ │ │
└─────────────────────┼──────────────────────┘
│
┌──────────▼──────────┐
│ KRWL3R CORE │
│ │
│ ┌───────────────┐ │
│ │ Orchestrator │ │
│ └───────┬───────┘ │
│ │ │
│ ┌──────┴──────┐ │
│ │ │ │
│ ┌─▼──┐ ┌───▼─┐ │
│ │Scrp│ │Pnch │ │
│ │lng │ │Tab │ │
│ └─┬──┘ └───┬─┘ │
│ │ │ │
└───┼─────────────┼───┘
│ │
┌──────▼──┐ ┌────▼─────┐
│ HTTP │ │ Headless │
│Requests │ │ Chrome │
└─────────┘ └──────────┘Layer 1 — Protocol Adapters: MCP, HTTP REST, ACP, and CLI interfaces that translate agent requests into unified internal calls.
Layer 2 — Core Orchestrator: Routes requests, manages concurrency, handles retries, and selects the optimal extraction strategy.
Layer 3 — Extraction Engines: Scrapling for fast HTTP-based extraction with auto-healing selectors. PinchTab for full browser control when JavaScript rendering or interaction is required.
Layer 4 — Transport: Raw HTTP requests for static content, headless Chrome instances for dynamic pages.
Powered By
KRWL3R stands on the shoulders of two exceptional open source projects:
Scrapling
D4Vinci/Scrapling — BSD-3-Clause — ~20k stars
An undetectable, powerful web scraping library with automatic anti-bot evasion and adaptive selectors that survive website changes. Scrapling's auto-healing selector engine is what makes KRWL3R resilient — when a site redesigns, selectors adapt instead of breaking.
PinchTab
pinchtab/pinchtab — MIT — ~3k stars
A Go-based browser control and text extraction engine that produces clean, ~800-token page representations. PinchTab's intelligent content extraction is what makes KRWL3R token-efficient — agents get structured content instead of raw HTML soup.
License
MIT — use it, fork it, ship it.
Contributing
Contributions are welcome. See docs/contributing.md for guidelines.
Quick version:
- Fork the repo
- Create a feature branch (
git checkout -b feat/my-feature) - Commit with conventional commits (
feat:,fix:,docs:,chore:) - Open a pull request
Please be respectful of the upstream projects (Scrapling and PinchTab) — KRWL3R integrates them, it does not fork or replace them.
<sub>// 2026 — built for the agent era</sub>