Skrape MCP Server

# Skrape MCP Server [](https://smithery.ai/server/@skrapeai/skrape-mcp) Convert any webpage into clean, LLM-ready Markdown using [skrape.ai](https://skrape.ai). Perfect for feeding web content into LLMs. This MCP server provides a simple interface to convert web pages to structured, clean Markdown format using the skrape.ai API. It's designed to work seamlessly with Claude Desktop, other LLMs, and MCP-compatible applications. <a href="https://glama.ai/mcp/servers/7i81qzgkzd"> <img width="380" height="200" src="https://glama.ai/mcp/servers/7i81qzgkzd/badge" /> </a> ## Why Use Skrape for LLM Integration? - **Clean, Structured Output**: Generates well-formatted Markdown that's ideal for LLM consumption - **Noise Reduction**: Automatically removes ads, navigation menus, and other irrelevant content - **Consistent Format**: Ensures web content is uniformly structured regardless of the source - **JavaScript Support**: Handles dynamic content by rendering JavaScript before conversion - **LLM-Optimized**: Perfect for feeding web content into LLMs like Claude, GPT, and other LLM models ## Features ### Tools - `get_markdown` - Convert any webpage to LLM-ready Markdown - Takes any input URL and optional parameters - Returns clean, structured Markdown optimized for LLM consumption - Supports JavaScript rendering for dynamic content - Optional JSON response format for advanced integrations ## Installation ### Installing via Smithery To install Skrape MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@skrapeai/skrape-mcp): ```bash npx -y @smithery/cli install @skrapeai/skrape-mcp --client claude ``` ### Manual Installation 1. Get your API key from [skrape.ai](https://skrape.ai) 1. Install dependencies: ```bash npm install ``` 1. Build the server: ```bash npm run build ``` 1. Add the server config to Claude Desktop: On MacOS: ```bash nano ~/Library/Application\ Support/Claude/claude_desktop_config.json ``` On Windows: ```bash notepad %APPDATA%/Claude/claude_desktop_config.json ``` Add this configuration (replace paths and API key with your values): ```json { "mcpServers": { "skrape": { "command": "node", "args": ["path/to/skrape-mcp/build/index.js"], "env": { "SKRAPE_API_KEY": "your-key-here" }, } } } ``` ## Using with LLMs Here's how to use the server with Claude or other LLM models: 1. First, ensure the server is properly configured in your LLM application 2. Then, you can ask the ALLMI to fetch and process any webpage: ``` Convert this webpage to markdown: https://example.com Claude will use the MCP tool like this: <use_mcp_tool> <server_name>skrape</server_name> <tool_name>get_markdown</tool_name> <arguments> { "url": "https://example.com", "options": { "renderJs": true } } </arguments> </use_mcp_tool> ``` The resulting Markdown will be clean, structured, and ready for LLM processing. ### Advanced Options The `get_markdown` tool accepts these parameters: - `url` (required): Any webpage URL to convert - `returnJson` (optional): Set to `true` to get the full JSON response instead of just markdown - `options` (optional): Additional scraping options - `renderJs`: Whether to render JavaScript before scraping (default: true) Example with all options: ``` <use_mcp_tool> <server_name>skrape</server_name> <tool_name>get_markdown</tool_name> <arguments> { "url": "https://example.com", "returnJson": true, "options": { "renderJs": false } } </arguments> </use_mcp_tool> ``` ## Development For development with auto-rebuild: ```bash npm run watch ``` ### Debugging Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector): ```bash npm run inspector ``` The Inspector will provide a URL to access debugging tools in your browser.