Crawleo MCP Server

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

Installation

Option 1: NPM (Recommended for local usage)

Install globally via npm:

npm install -g crawleo-mcp

Or use npx without installing:

npx crawleo-mcp

Option 2: Clone Repository

git clone https://github.com/Crawleo/Crawleo-MCP.git
cd Crawleo-MCP
npm install
npm run build

Option 3: Docker

Build and run using Docker:

# Build the image
docker build -t crawleo-mcp .

# Run with your API key
docker run -e CRAWLEO_API_KEY=your_api_key crawleo-mcp

Docker configuration for MCP clients:

{
  "mcpServers": {
    "crawleo": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "CRAWLEO_API_KEY=YOUR_API_KEY_HERE", "crawleo-mcp"]
    }
  }
}

Option 4: Remote Server (No installation needed)

Use the hosted version at https://api.crawleo.dev/mcp - see configuration examples below.

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_)

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):

{
  "mcpServers": {
    "crawleo": {
      "command": "npx",
      "args": ["crawleo-mcp"],
      "env": {
        "CRAWLEO_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "crawleo": {
      "command": "crawleo-mcp",
      "env": {
        "CRAWLEO_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

From cloned repository:

{
  "mcpServers": {
    "crawleo": {
      "command": "node",
      "args": ["/path/to/Crawleo-MCP/dist/index.js"],
      "env": {
        "CRAWLEO_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

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:

{
  "mcpServers": {
    "crawleo": {
      "url": "https://api.crawleo.dev/mcp",
      "transport": "http",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}

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:

"Search for the latest AI news and summarize the top 5 articles"
"Find Python web scraping tutorials and extract code examples"

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:

{
  "mcpServers": {
    "crawleo": {
      "url": "https://api.crawleo.dev/mcp",
      "transport": "http",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}

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:

"Search for React best practices and add them to my code comments"
"Find the latest documentation for this API endpoint"

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:

{
  "mcpServers": {
    "crawleo": {
      "url": "https://api.crawleo.dev/mcp",
      "transport": "http",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}

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

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:

{
  "servers": {
    "Crawleo": {
      "url": "https://api.crawleo.dev/mcp",
      "transport": "http",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}

Complete example with multiple servers:

{
  "servers": {
    "Crawleo": {
      "url": "https://api.crawleo.dev/mcp",
      "transport": "http",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY_HERE"
      }
    }
  }
}

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!

Example usage:

Ask Copilot: "Search for the latest Python best practices"
Ask Copilot: "Find documentation for this library"

5. OpenAI Platform (Direct Integration)

OpenAI now supports MCP servers directly! Here's how to use Crawleo with OpenAI's API:

Python Example:

from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model="gpt-4",
    input=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_text",
                    "text": "search for latest news about openai models"
                }
            ]
        }
    ],
    text={
        "format": {
            "type": "text"
        },
        "verbosity": "medium"
    },
    reasoning={
        "effort": "medium"
    },
    tools=[
        {
            "type": "mcp",
            "server_label": "Crawleo",
            "server_url": "https://api.crawleo.dev/mcp",
            "server_description": "Crawleo MCP Server - Real-Time Web Knowledge for AI",
            "authorization": "YOUR_API_KEY_HERE",
            "allowed_tools": [
                "web.search",
                "web.crawl"
            ],
            "require_approval": "always"
        }
    ],
    store=True,
    include=[
        "reasoning.encrypted_content",
        "web_search_call.action.sources"
    ]
)

print(response)

Key Parameters:

• server_url - Crawleo MCP endpoint
• authorization - Your Crawleo API key
• allowed_tools - Enable web.search and/or web.crawl
• require_approval - Set to "always", "never", or "conditional"

Node.js Example:

import OpenAI from 'openai';

const client = new OpenAI();

const response = await client.responses.create({
  model: 'gpt-4',
  input: [
    {
      role: 'user',
      content: [
        {
          type: 'input_text',
          text: 'search for latest AI developments'
        }
      ]
    }
  ],
  tools: [
    {
      type: 'mcp',
      server_label: 'Crawleo',
      server_url: 'https://api.crawleo.dev/mcp',
      server_description: 'Crawleo MCP Server - Real-Time Web Knowledge for AI',
      authorization: 'YOUR_API_KEY_HERE',
      allowed_tools: ['web.search', 'web.crawl'],
      require_approval: 'always'
    }
  ]
});

console.log(response);

Available Tools

web.search

Search the web in real-time with customizable parameters.

Parameters:

• query (required) - Search term
• max_pages - Number of result pages (default: 1)
• setLang - Language code (e.g., "en", "ar")
• cc - Country code (e.g., "US", "EG")
• device - Device type: "desktop", "mobile", "tablet" (default: "desktop")
• enhanced_html - Get clean HTML (default: true)
• raw_html - Get raw HTML (default: false)
• markdown - Get Markdown format (default: true)
• page_text - Get plain text (default: false)
• auto_crawling - Auto-crawl result URLs (default: false)

Example:

Ask your AI: "Search for 'Python web scraping' and return results in Markdown"

web.crawl

Extract content from specific URLs.

Parameters:

• urls (required) - List of URLs to crawl
• rawHtml - Return raw HTML (default: false)
• markdown - Convert to Markdown (default: false)
• screenshot - Capture screenshot (optional)
• country - Geographic location

Example:

Ask your AI: "Crawl https://example.com and extract the main content in Markdown"

Troubleshooting

MCP server not appearing