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crawl4ai-mcp
A Model Context Protocol (MCP) server implementation that integrates Crawl4AI with Cursor AI, providing web scraping and crawling capabilities as tools for LLMs in Cursor Composer's agent mode.
Python 3.10 or higher installed.
Basic setup instructions also available in the Official Docs for MCP Server QuickStart.
First, let's install uv and set up our Python project and environment:
MacOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Make sure to restart your terminal afterwards to ensure that the uv command gets picked up.
After that:
Clone the repository
Install dependencies using UV:
# Navigate to the crawl4ai-mcp directory
cd crawl4ai-mcp
# Install dependencies (Only first time)
uv venv
uv sync
# Activate the venv
source .venv/bin/activate
# Run the server
python main.py
You may need to put the full path to the uv executable in the command field. You can get this by running which uv on MacOS/Linux or where uv on Windows.
{
"mcpServers": {
"Crawl4AI": {
"command": "uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/crawl4ai-mcp",
"run",
"main.py"
]
}
}
}
This MCP server exposes the following tools to the LLM:
scrape_webpage(url: str)
url (string, required): The URL of the webpage to scrape.TextContent object with the scraped content (primarily markdown) as JSON.crawl_website(url: str, crawl_depth: int = 1, max_pages: int = 5)
url (string, required): The starting URL to crawl.crawl_depth (integer, optional, default: 1): The maximum depth to crawl relative to the starting URL.max_pages (integer, optional, default: 5): The maximum number of pages to scrape during the crawl.TextContent object with a JSON array of results for the crawled pages (including URL, success status, markdown content, or error).Run Claude Code as an MCP server so any agent can delegate coding tasks to it
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