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Scrapling

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Adaptive web scraping framework for effortless data extraction.

MCP ServerSearch & WebLocal (stdio) 63.8k
View on GitHub
Updated 2026-06-15

What is the Scrapling MCP server?

Scrapling supports multiple fetchers including StealthyFetcher and DynamicFetcher for reliable data collection under the radar. It features an adaptive selection system that saves and recovers elements even after site redesigns.

The spider architecture allows scaling to multi-session crawls with pause/resume functionality, real-time stats, and streaming output, all accessible via a simple Python API.

Install & connect

Add this to your MCP client config. Pick your client below and copy.

{
  "mcpServers": {
    "Scrapling": {
      "command": "uvx",
      "args": [
        "scrapling"
      ]
    }
  }
}

Package: scrapling (pypi)

Other ways to install

pip

pip
pip install scrapling

Example prompts

Once connected, try asking your AI client:

Scrape product listings from example.com and save them adaptively
Start a spider crawl on a news site with proxy rotation enabled
Fetch a page stealthily and extract all links that survive layout changes
Show me how to use adaptive mode on a previously scraped response

Security & permissions

Runs locally via stdio with no API keys required. Needs network access for web fetching and a Python environment with the Scrapling package installed.

What you can do with Scrapling

E-commerce monitoring

Track product prices and availability on sites that frequently update layouts using adaptive CSS selectors.

Large-scale crawling

Run concurrent spiders with automatic proxy rotation and pause/resume for extensive data collection jobs.

Anti-bot bypassing

Fetch protected pages using StealthyFetcher or DynamicFetcher without additional configuration.

How to use Scrapling

  1. 1Install Scrapling via pip in your Python environment
  2. 2Configure the MCP server entrypoint using the stdio transport
  3. 3Add the server to your MCP client configuration file
  4. 4Restart the client and verify the connection
  5. 5Use natural language prompts to trigger scraping tasks

Scrapling: pros & cons

Pros

  • +Adaptive parsing survives website changes automatically
  • +Built-in bypass for common anti-bot protections
  • +Scalable spider framework with proxy and session management
  • +Fast performance with real-time stats and streaming support

Cons

  • Primarily a Python library requiring code familiarity
  • MCP integration details are in separate documentation
  • Stealth features may need tuning for specific targets
Did you find this helpful?

Frequently asked questions

No, it operates locally and uses no external API keys.

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