A Model Context Protocol (MCP) integration for Scraper.is - A powerful web scraping tool for AI assistants.

This package allows AI assistants to scrape web content through the MCP protocol, enabling them to access up-to-date information from the web.

• 🌐 Web Scraping: Extract content from any website
• 📸 Screenshots: Capture visual representations of web pages
• 📄 Multiple Formats: Get content in markdown, HTML, or JSON
• 🔄 Progress Updates: Real-time progress reporting during scraping operations
• 🔌 MCP Integration: Seamless integration with MCP-compatible AI assistants

To install scaperis-mcp for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Ai-Quill/scaperis-mcp --client claude

npm install -g scraperis-mcp

Or with yarn:

yarn global add scraperis-mcp

You need a Scraper.is API key to use this package.

1. Sign up or log in at scraper.is
2. Navigate to the API Keys section in your dashboard: https://www.scraper.is/dashboard/apikeys
3. Create a new API key or copy your existing key
4. Store this key securely as you'll need it to use this package

Create a .env file with your Scraper.is API key:

SCRAPERIS_API_KEY=your_api_key_here

To use this package with Claude Desktop:

1. Install the package globally:

   npm install -g scraperis-mcp

2. Add the following configuration to your claude_desktop_config.json file:

   {
     "mcpServers": {
       "scraperis_scraper": {
         "command": "scraperis-mcp",
         "args": [],
         "env": {
           "SCRAPERIS_API_KEY": "your-api-key-here",
           "DEBUG": "*"
         }
       }
     }
   }

3. Replace your-api-key-here with your actual Scraper.is API key.

4. Restart Claude Desktop to apply the changes.

For development and testing, you can use the MCP Inspector:

npx @modelcontextprotocol/inspector scraperis-mcp

This package is designed to be used with AI assistants that support the Model Context Protocol (MCP). When properly configured, the AI assistant can use the following tools:

The scrape tool allows the AI to extract content from websites. It supports various formats:

• markdown: Returns the content in markdown format
• html: Returns the content in HTML format
• screenshot: Returns a screenshot of the webpage
• json: Returns structured data in JSON format

Example prompt for the AI:

Can you scrape the latest news from techcrunch.com and summarize it for me?

Scrapes content from a webpage based on a prompt.

Parameters:

• prompt (string): The prompt describing what to scrape, including the URL
• format (string): The format to return the content in (markdown, html, screenshot, json, quick)

Example:

{
  "prompt": "Get me the top 10 products from producthunt.com",
  "format": "markdown"
}

1. Clone the repository:

   git clone https://github.com/Ai-Quill/scraperis-mcp.git
   cd scraperis-mcp

2. Install dependencies:

   npm install

3. Build the project:

   npm run build

• npm run build: Build the project
• npm run watch: Watch for changes and rebuild
• npm run dev: Run with MCP Inspector for development
• npm run test: Run tests
• npm run lint: Run ESLint

Contributions are welcome! Please feel free to submit a Pull Request.

This project is licensed under the MIT License - see the LICENSE file for details.

• Model Context Protocol
• Scraper.is