Web Crawler MCP Server
@JonathanHsuHH
About Web Crawler MCP Server
A MCP server that provides a web crawling and content extraction tool for AI assistants
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"web-crawler-mcp-server": {
"command": "node",
"args": [
"build/index.js"
]
}
}
}Tools
2** Extracts and returns the cleaned text content from a specified URL.
`url` (string, required): The URL to extract content from.
Overview
What is Web Crawler MCP Server?
A Model Context Protocol (MCP) server that provides a web crawling and content extraction tool for AI assistants such as Claude Desktop, Cursor, and other MCP-compatible clients. It extracts and cleans main text content from any public web page.
How to use Web Crawler MCP Server?
Install dependencies with npm install, build with npm run build, then run directly with node build/index.js. Alternatively, configure it as an MCP server in your client (e.g., Claude Desktop) by adding a JSON entry that points command and args to the built server.
Key features of Web Crawler MCP Server
- Extracts and cleans main text content from public web pages.
- Uses Puppeteer with stealth plugin to bypass anti-bot protections.
- Returns readable, whitespace-normalized text for LLM consumption.
- Easy integration with Claude Desktop, Cursor, and other MCP clients.
- Launches a real browser instance (
headless: false) for best compatibility.
Use cases of Web Crawler MCP Server
- An AI assistant fetching and reading article text from a news URL.
- A developer integrating web page content extraction into an MCP-compatible toolchain.
- Enabling LLMs to consume clean, normalized text from any public website.
FAQ from Web Crawler MCP Server
What dependencies are required to run Web Crawler MCP Server?
Node.js v16 or higher, and an MCP-compatible client. Some Linux environments may require additional Puppeteer dependencies.
What output format does the server return?
The server returns plain, whitespace-normalized text, suitable for LLM input.
How does the server handle anti-bot protections?
It uses Puppeteer with a stealth plugin to bypass common anti-bot measures.
Can I customize the parsing logic?
Yes, for advanced parsing you can modify the Cheerio logic in src/index.ts.
What transport or authentication does the server use?
The README does not mention any transport or authentication configuration; it is intended to be configured as a local MCP server via stdin/stdout.
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