Crawleo/Crawleo-MCP

Real-time web search and crawling capabilities for AI assistants through Model Context Protocol (MCP).
Overview
Crawleo MCP enables AI assistants to access live web data through two powerful tools:
- **web.search** - Real-time web search with multiple output formats
- **web.crawl** - Deep content extraction from any URL
Features
✅ **Real-time web search** from any country/language
✅ **Multiple output formats** - Enhanced HTML, Raw HTML, Markdown, Plain Text
✅ **Device-specific results** - Desktop, mobile, or tablet view
✅ **Deep content extraction** with JavaScript rendering
✅ **Zero data retention** - Complete privacy
✅ **Auto-crawling** option for search results
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Installation
Option 1: NPM (Recommended for local usage)
Install globally via npm:
Or use npx without installing:
Option 2: Clone Repository
Option 3: Docker
Build and run using Docker:
**Docker configuration for MCP clients:**
Option 4: Remote Server (No installation needed)
Use the hosted version at https://api.crawleo.dev/mcp - see configuration examples below.
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Getting Your API Key
1. Visit crawleo.dev
2. Sign up for a free account
3. Navigate to your dashboard
4. Copy your API key (starts with sk_)
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Setup Instructions
Using Local MCP Server (npm package)
After installing via npm, configure your MCP client to use the local server:
**Claude Desktop / Cursor / Windsurf (Local):**
**Or if installed globally:**
**From cloned repository:**
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Using Remote Server (Hosted)
1. Claude Desktop
**Location of config file:**
- **macOS**: ~/Library/Application Support/Claude/claude_desktop_config.json
- **Windows**: %APPDATA%\Claude\claude_desktop_config.json
- **Linux**: ~/.config/Claude/claude_desktop_config.json
**Configuration:**
Replace YOUR_API_KEY_HERE with your actual API key from crawleo.dev.
**Steps:**
1. Open the config file in a text editor
2. Add the Crawleo MCP configuration
3. Save the file
4. Restart Claude Desktop completely (quit and reopen)
5. Start a new conversation and ask Claude to search the web!
**Example usage:**
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2. Cursor IDE
**Location of config file:**
- **macOS**: ~/.cursor/config.json or ~/Library/Application Support/Cursor/config.json
- **Windows**: %APPDATA%\Cursor\config.json
- **Linux**: ~/.config/Cursor/config.json
**Configuration:**
**Steps:**
1. Locate and open your Cursor config file
2. Add the Crawleo MCP configuration
3. Save the file
4. Restart Cursor
5. The MCP tools will be available in your AI assistant
**Example usage in Cursor:**
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3. Windsurf IDE
**Location of config file:**
- **macOS**: ~/Library/Application Support/Windsurf/config.json
- **Windows**: %APPDATA%\Windsurf\config.json
- **Linux**: ~/.config/Windsurf/config.json
**Configuration:**
**Steps:**
1. Open the Windsurf config file
2. Add the Crawleo MCP server configuration
3. Save and restart Windsurf
4. Start using web search in your coding workflow
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4. GitHub Copilot
**Location of config file:**
For GitHub Copilot in VS Code or compatible editors, you need to configure MCP servers.
**Configuration:**
Create or edit your MCP config file and add:
**Complete example with multiple servers:**
**Steps:**
1. Open your GitHub Copilot MCP configuration
2. Add the Crawleo server configuration
3. Save the file
4. Restart VS Code or your IDE
5. GitHub Copilot can now use Crawleo for web searches!