README.md•3.59 kB
# Skrape MCP Server
[](https://smithery.ai/server/@skrapeai/skrape-mcp)
Convert webpages into clean, LLM-ready Markdown using [skrape.ai](https://skrape.ai). An MCP server that seamlessly integrates web scraping with Claude Desktop and other MCP-compatible applications.
## Key Features
- **Clean Output**: Removes ads, navigation, and irrelevant content
- **JavaScript Support**: Handles dynamic content rendering
- **LLM-Optimized**: Structured Markdown perfect for AI consumption
- **Consistent Format**: Uniform structure regardless of source
## 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.
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