About Scrapling Fetch MCP
Scrapling Fetch MCP is an MCP server that helps AI assistants fetch text content from bot-protected websites. It is intended for low-volume retrieval of documentation and reference material rather than large-scale scraping.
Key features
- 01Fetches pages protected by anti-automation measures
- 02Returns clean HTML or Markdown output
- 03Supports pagination for complete page retrieval
- 04Extracts content matching a regular expression
- 05Escalates through three protection levels automatically
Use cases
- 01Fetching API documentation or reference pages
- 02Finding specific mentions on a web page
- 03Retrieving installation instructions from protected sites
MCP support
The project is an MCP server that exposes two tools to MCP clients: page fetching and pattern extraction.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEscrapling-fetch-mcp
Helps AI assistants fetch content from bot-protected websites. Uses Scrapling (patchright + curl-cffi) to bypass anti-automation measures, returning clean HTML or Markdown.
Optimized for low-volume retrieval of documentation and reference materials. Not designed for high-volume scraping or data harvesting.
Requirements: Python 3.10+, uv
Claude Code Skill
The easiest way to use this is as a Claude Code skill. Once installed, Claude will automatically fetch bot-protected URLs when you ask — no manual commands needed.
Install into your project (recommended — only loads in this project's context):
git clone --depth=1 https://github.com/cyberchitta/scrapling-fetch-mcp /tmp/scrapling-fetch-mcp
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch .claude/skills/
rm -rf /tmp/scrapling-fetch-mcp
Or install for all projects (loads into context everywhere):
git clone --depth=1 https://github.com/cyberchitta/scrapling-fetch-mcp /tmp/scrapling-fetch-mcp
cp -r /tmp/scrapling-fetch-mcp/skills/s-fetch ~/.claude/skills/
rm -rf /tmp/scrapling-fetch-mcp
The first time you invoke /s-fetch, Claude will read
skills/s-fetch/references/install.md and run the one-time setup
(installs the tool and downloads browser binaries). After that, just
ask naturally:
"Fetch the docs at https://example.com/api"
"Find all mentions of 'authentication' on that page"
"Get me the installation instructions from their homepage"
Claude Desktop (MCP Server)
If the /s-fetch skill has already installed the tool, skip to the config below.
Otherwise install first:
uv tool install git+https://github.com/cyberchitta/scrapling-fetch-mcp
uvx --from git+https://github.com/cyberchitta/scrapling-fetch-mcp scrapling install
Note: Browser installation downloads hundreds of MB and must complete before first use. If the server times out initially, wait a few minutes and try again.
Add this to your Claude Desktop MCP settings and restart:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"scrapling-fetch": {
"command": "uvx",
"args": ["scrapling-fetch-mcp"]
}
}
}
How It Works
Two tools, used automatically by Claude:
- Page fetching — retrieves complete pages with pagination support
- Pattern extraction — finds content matching a regex
Three protection levels, escalated automatically:
- basic — fast (1-2s), works for most sites
- stealth — moderate (3-8s), headless Chromium
- max-stealth — thorough (10s+), full browser fingerprint
Limitations
- Text content only (documentation, articles, references)
- Not for high-volume scraping or sites requiring authentication
- Performance varies by site complexity and protection level
License
Apache 2.0
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.