Scrapling Web Scraping
v0.4.2Advanced web scraping with Scrapling — MCP-native guidance for extraction, crawling, and anti-bot handling. Use via mcporter (MCP) to call the `scrapling` MC...
MIT-0
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the contents: the SKILL.md, reference docs, and scripts all focus on scrapling usage, MCP setup, fetcher selection, anti-bot escalation, proxy rotation, and spider recipes. The included Python helpers import scrapling.fetchers as expected. There are no unrelated environment variables, binaries, or surprising install requirements declared.
Instruction Scope
Runtime instructions and examples show network activity (fetch_page, fetch_dynamic, fetch_stealthy), proxy rotation, and anti-bot bypass features — all coherent with a scraping skill. The docs explicitly advise authorization and include 'do not bypass paywalls' guidance. Note: the instructions and scripts will fetch arbitrary URLs and write crawl/download dirs (e.g., crawldir, downloads), so running them can retrieve remote HTML/assets and store them locally; this is expected but worth being aware of.
Install Mechanism
This is instruction-only (no install spec). The README suggests installing via pip (pip install scrapling[...] and playwright). That is a standard, traceable install mechanism; the skill itself does not download arbitrary remote archives or run unusual installers.
Credentials
The skill does not declare required environment variables or credentials. Docs show an optional PYTHONPATH env in an MCP config example and proxy examples that may include user:pass proxies (these are examples only). There is no unexplained request for tokens/keys in package metadata.
Persistence & Privilege
always is false and the skill does not request any elevated platform privileges. It does not modify other skills' configurations. The skill will run code when invoked (including network fetches) but does not demand permanent inclusion or special privileges.
Assessment
This package appears coherent with a web-scraping helper, but review these before installing or running: 1) Legal/ethical: only scrape sites you are authorized to access; the skill documents anti-bot and proxy techniques that can be abused — do not use them to evade protections. 2) Package provenance: the SKILL references a GitHub repo — verify the upstream project and author before pip installing (and check the package version matches the skill metadata). 3) Proxy credentials: proxy examples may include user:pass; never store secrets in plaintext or share them with the skill unless you understand where they're used. 4) Isolation: run scrapling and Playwright in an isolated environment (sandbox/VM/CI) because the scripts will fetch arbitrary URLs and write files (crawldir, downloads). 5) Review inconsistencies: the included _meta.json shows a different ownerId/version than the registry metadata — confirm which source/version you trust. If you need higher assurance, inspect the upstream scrapling code on the referenced GitHub and run the helper scripts locally in a controlled environment before enabling the skill for autonomous use.Like a lobster shell, security has layers — review code before you run it.
latest
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
SKILL.md
Scrapling MCP — Web Scraping Guidance
Guidance Layer + MCP Integration
Use this skill for strategy and patterns. For execution, call Scrapling's MCP server viamcporter.
Quick Start (MCP)
1. Install Scrapling with MCP support
pip install scrapling[mcp]
# Or for full features:
pip install scrapling[mcp,playwright]
python -m playwright install chromium
2. Add to OpenClaw MCP config
{
"mcpServers": {
"scrapling": {
"command": "python",
"args": ["-m", "scrapling.mcp"]
}
}
}
3. Call via mcporter
mcporter call scrapling fetch_page --url "https://example.com"
Execution vs Guidance
| Task | Tool | Example |
|---|---|---|
| Fetch a page | mcporter | mcporter call scrapling fetch_page --url URL |
| Extract with CSS | mcporter | mcporter call scrapling css_select --selector ".title::text" |
| Which fetcher to use? | This skill | See "Fetcher Selection Guide" below |
| Anti-bot strategy? | This skill | See "Anti-Bot Escalation Ladder" |
| Complex crawl patterns? | This skill | See "Spider Recipes" |
Fetcher Selection Guide
┌─────────────────┐ ┌──────────────────┐ ┌──────────────────┐
│ Fetcher │────▶│ DynamicFetcher │────▶│ StealthyFetcher │
│ (HTTP) │ │ (Browser/JS) │ │ (Anti-bot) │
└─────────────────┘ └──────────────────┘ └──────────────────┘
Fastest JS-rendered Cloudflare,
Static pages SPAs, React/Vue Turnstile, etc.
Decision Tree
- Static HTML? →
Fetcher(10-100x faster) - Need JS execution? →
DynamicFetcher - Getting blocked? →
StealthyFetcher - Complex session? → Use Session variants
MCP Fetch Modes
fetch_page— HTTP fetcherfetch_dynamic— Browser-based with Playwrightfetch_stealthy— Anti-bot bypass mode
Anti-Bot Escalation Ladder
Level 1: Polite HTTP
# MCP call: fetch_page with options
{
"url": "https://example.com",
"headers": {"User-Agent": "..."},
"delay": 2.0
}
Level 2: Session Persistence
# Use sessions for cookie/state across requests
FetcherSession(impersonate="chrome") # TLS fingerprint spoofing
Level 3: Stealth Mode
# MCP: fetch_stealthy
StealthyFetcher.fetch(
url,
headless=True,
solve_cloudflare=True, # Auto-solve Turnstile
network_idle=True
)
Level 4: Proxy Rotation
See references/proxy-rotation.md
Adaptive Scraping (Anti-Fragile)
Scrapling can survive website redesigns using adaptive selectors:
# First run — save fingerprints
products = page.css('.product', auto_save=True)
# Later runs — auto-relocate if DOM changed
products = page.css('.product', adaptive=True)
MCP usage:
mcporter call scrapling css_select \\
--selector ".product" \\
--adaptive true \\
--auto-save true
Spider Framework (Large Crawls)
When to use Spiders vs direct fetching:
- ✅ Spider: 10+ pages, concurrency needed, resume capability, proxy rotation
- ✅ Direct: 1-5 pages, quick extraction, simple flow
Basic Spider Pattern
from scrapling.spiders import Spider, Response
class ProductSpider(Spider):
name = "products"
start_urls = ["https://example.com/products"]
concurrent_requests = 10
download_delay = 1.0
async def parse(self, response: Response):
for product in response.css('.product'):
yield {
"name": product.css('h2::text').get(),
"price": product.css('.price::text').get(),
"url": response.url
}
# Follow pagination
next_page = response.css('.next a::attr(href)').get()
if next_page:
yield response.follow(next_page)
# Run with resume capability
result = ProductSpider(crawldir="./crawl_data").start()
result.items.to_jsonl("products.jsonl")
Advanced: Multi-Session Spider
from scrapling.spiders import Spider, Request, Response
from scrapling.fetchers import FetcherSession, AsyncStealthySession
class MultiSessionSpider(Spider):
name = "multi"
start_urls = ["https://example.com/"]
def configure_sessions(self, manager):
manager.add("fast", FetcherSession(impersonate="chrome"))
manager.add("stealth", AsyncStealthySession(headless=True), lazy=True)
async def parse(self, response: Response):
for link in response.css('a::attr(href)').getall():
if "/protected/" in link:
yield Request(link, sid="stealth")
else:
yield Request(link, sid="fast")
Spider Features
- Pause/Resume:
crawldirparameter saves checkpoints - Streaming:
async for item in spider.stream()for real-time processing - Auto-retry: Configurable retry on blocked requests
- Export: Built-in
to_json(),to_jsonl()
CLI & Interactive Shell
Terminal Extraction (No Code)
# Extract to markdown
scrapling extract get 'https://example.com' content.md
# Extract specific element
scrapling extract get 'https://example.com' content.txt \\
--css-selector '.article' \\
--impersonate 'chrome'
# Stealth mode
scrapling extract stealthy-fetch 'https://protected.com' content.md \\
--no-headless \\
--solve-cloudflare
Interactive Shell
scrapling shell
# Inside shell:
>>> page = Fetcher.get('https://example.com')
>>> page.css('h1::text').get()
>>> page.find_all('div', class_='item')
Parser API (Beyond CSS/XPath)
BeautifulSoup-Style Methods
# Find by attributes
page.find_all('div', {'class': 'product', 'data-id': True})
page.find_all('div', class_='product', id=re.compile(r'item-\\d+'))
# Text search
page.find_by_text('Add to Cart', tag='button')
page.find_by_regex(r'\\$\\d+\\.\\d{2}')
# Navigation
first = page.css('.product')[0]
parent = first.parent
siblings = first.next_siblings
children = first.children
# Similarity
similar = first.find_similar() # Find visually/structurally similar elements
below = first.below_elements() # Elements below in DOM
Auto-Generated Selectors
# Get robust selector for any element
element = page.css('.product')[0]
selector = element.auto_css_selector() # Returns stable CSS path
xpath = element.auto_xpath()
Proxy Rotation
from scrapling.spiders import ProxyRotator
# Cyclic rotation
rotator = ProxyRotator([
"http://proxy1:8080",
"http://proxy2:8080",
"http://user:pass@proxy3:8080"
], strategy="cyclic")
# Use with any session
with FetcherSession(proxy=rotator.next()) as session:
page = session.get('https://example.com')
Common Recipes
Pagination Patterns
# Page numbers
for page_num in range(1, 11):
url = f"https://example.com/products?page={page_num}"
...
# Next button
while next_page := response.css('.next a::attr(href)').get():
yield response.follow(next_page)
# Infinite scroll (DynamicFetcher)
with DynamicSession() as session:
page = session.fetch(url)
page.scroll_to_bottom()
items = page.css('.item').getall()
Login Sessions
with StealthySession(headless=False) as session:
# Login
login_page = session.fetch('https://example.com/login')
login_page.fill('input[name="username"]', 'user')
login_page.fill('input[name="password"]', 'pass')
login_page.click('button[type="submit"]')
# Now session has cookies
protected_page = session.fetch('https://example.com/dashboard')
Next.js Data Extraction
# Extract JSON from __NEXT_DATA__
import json
import re
next_data = json.loads(
re.search(
r'__NEXT_DATA__" type="application/json">(.*?)</script>',
page.html_content,
re.S
).group(1)
)
props = next_data['props']['pageProps']
Output Formats
# JSON (pretty)
result.items.to_json('output.json')
# JSONL (streaming, one per line)
result.items.to_jsonl('output.jsonl')
# Python objects
for item in result.items:
print(item['title'])
Performance Tips
- Use HTTP fetcher when possible — 10-100x faster than browser
- Impersonate browsers —
impersonate='chrome'for TLS fingerprinting - HTTP/3 support —
FetcherSession(http3=True) - Limit resources —
disable_resources=Truein Dynamic/Stealthy - Connection pooling — Reuse sessions across requests
Guardrails (Always)
- Only scrape content you're authorized to access
- Respect robots.txt and ToS
- Add delays (
download_delay) for large crawls - Don't bypass paywalls or authentication without permission
- Never scrape personal/sensitive data
References
references/mcp-setup.md— Detailed MCP configurationreferences/anti-bot.md— Anti-bot handling strategiesreferences/proxy-rotation.md— Proxy setup and rotationreferences/spider-recipes.md— Advanced crawling patternsreferences/api-reference.md— Quick API referencereferences/links.md— Official docs links
Scripts
scripts/scrapling_scrape.py— Quick one-off extractionscripts/scrapling_smoke_test.py— Test connectivity and anti-bot indicators
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