About scrapling-mcp
scrapling-mcp is a web-scraping guidance skill for choosing fetch strategies and crawl patterns. It pairs with Scrapling’s MCP server, called through mcporter, for executing requests and extraction.
Key features
- 01Fetcher selection guidance
- 02Anti-bot escalation patterns
- 03Adaptive selector guidance
- 04Spider crawl recipes
- 05Parser and extraction references
Use cases
- 01Choosing a fetch mode for a site
- 02Planning extraction across many pages
- 03Handling changing page layouts
- 04Selecting strategies for blocked requests
MCP support
The skill provides guidance rather than performing scraping. It directs execution to Scrapling’s MCP server through mcporter, including page fetching and CSS selection.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ devbd1/ skills --skill scrapling-mcpAfter installing, type/scrapling-mcpin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/anti-bot.mdapi_reference.mdlinks.mdmcp-setup.mdproxy-rotation.mdrecipes.mdspider-recipes.mdscripts/scrapling_scrape.pyscrapling_smoke_test.pyDetails
From the project READMEScrapling MCP — Web Scraping Guidance
Source repo: https://github.com/DevBD1/skills/tree/main/openclaw-skill-scrapling-mcp
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