by crawleo
Crawleo — real-time web search and website crawling with zero data retention. Fast, private site crawling and live searc
Enables AI assistants to perform real-time web searches and extract content from websites with JavaScript rendering support. Offers multiple output formats and ensures zero data retention for privacy.
Crawleo is an official MCP server published by crawleo that provides AI assistants with tools and capabilities via the Model Context Protocol. Crawleo — real-time web search and website crawling with zero data retention. Fast, private site crawling and live searc It is categorized under search web.
You can install Crawleo in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
MIT
Crawleo is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
Crawleo is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Crawleo is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend Crawleo for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Crawleo is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated Crawleo against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Crawleo is the kind of server we cite when onboarding engineers to host + tool permissions.
Useful MCP listing: Crawleo is the kind of server we cite when onboarding engineers to host + tool permissions.
Crawleo has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Crawleo benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Crawleo is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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Real-time web search and crawling capabilities for AI assistants through Model Context Protocol (MCP).
Crawleo MCP enables AI assistants to access live web data through two powerful tools:
✅ 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
Install globally via npm:
npm install -g crawleo-mcp
Or use npx without installing:
npx crawleo-mcp
git clone https://github.com/Crawleo/Crawleo-MCP.git
cd Crawleo-MCP
npm install
npm run build
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"]
}
}
}
Use the hosted version at https://api.crawleo.dev/mcp - see configuration examples below.
sk_)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"
}
}
}
}
Location of config file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonConfiguration:
{
"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:
Example usage:
"Search for the latest AI news and summarize the top 5 articles"
"Find Python web scraping tutorials and extract code examples"
Location of config file:
~/.cursor/config.json or ~/Library/Application Support/Cursor/config.json%APPDATA%\Cursor\config.json~/.config/Cursor/config.jsonConfiguration:
{
"mcpServers": {
"crawleo": {
"url": "https://api.crawleo.dev/mcp",
"transport": "http",
"headers": {
"Authorization": "Bearer YOUR_API_KEY_HERE"
}
}
}
}
Steps:
Example usage in Cursor:
"Search for React best practices and add them to my code comments"
"Find the latest documentation for this API endpoint"
Location of config file:
~/Library/Application Support/Windsurf/config.json%APPDATA%\Windsurf\config.json~/.config/Windsurf/config.jsonConfiguration:
{
"mcpServers": {
"crawleo": {
"url": "https://api.crawleo.dev/mcp",
"transport": "http",
"headers": {
"Authorization": "Bearer YOUR_API_KEY_HERE"
}
}
}
}
Steps:
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:
Example usage:
Ask Copilot: "Search for the latest Python best practices"
Ask Copilot: "Find documentation for this library"
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 endpointauthorization - Your Crawleo API keyallowed_tools - Enable web.search and/or web.crawlrequire_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);
Search the web in real-time with customizable parameters.
Parameters:
query (required) - Search termmax_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"
Extract content from specific URLs.
Parameters:
urls (required) - List of URLs to crawlrawHtml - Return raw HTML (default: false)markdown - Convert to Markdown (default: false)screenshot - Capture screenshot (optional)country - Geographic locationExample:
Ask your AI: "Crawl https://example.com and extract the main content in Markdown"
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.