io.github.Crawleo/Crawleo-MCP

编码与调试

by crawleo

托管版 Crawleo MCP,提供可远程流式访问的 HTTP endpoint,便于集成调用。

什么是 io.github.Crawleo/Crawleo-MCP

托管版 Crawleo MCP,提供可远程流式访问的 HTTP endpoint,便于集成调用。

README

Crawleo MCP Server

<a href="https://glama.ai/mcp/servers/@crawleo/crawleo-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@crawleo/crawleo-mcp/badge" alt="Crawleo MCP server" /> </a>

smithery badge

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:

bash
npm install -g crawleo-mcp

Or use npx without installing:

bash
npx crawleo-mcp

Option 2: Clone Repository

bash
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:

bash
# 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:

json
{
  "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):

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

Or if installed globally:

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

From cloned repository:

json
{
  "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:

json
{
  "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:

code
"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:

json
{
  "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:

code
"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:

json
{
  "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:

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

Complete example with multiple servers:

json
{
  "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:

code
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:

python
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:

javascript
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:

code
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:

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

Troubleshooting

MCP server not appearing

  1. Check config file location - Make sure you're editing the correct file
  2. Verify JSON syntax - Use a JSON validator to check for syntax errors
  3. Restart the application - Completely quit and reopen (not just reload)
  4. Check API key - Ensure your API key is valid and active at crawleo.dev

Authentication errors

  • Verify your API key is correct (should start with sk_)
  • Make sure the key is wrapped in quotes
  • Check that "Bearer " prefix is included in the Authorization header (for Claude/Cursor/Windsurf)
  • For OpenAI Platform, use the key directly in the authorization field
  • Confirm your account has available credits at crawleo.dev

No results returned

  • Check your internet connection
  • Verify the search query is not empty
  • Try a simpler search query first
  • Check API status at crawleo.dev

Tool names not recognized

Make sure you're using the correct tool names:

  • Use web.search (not search_web)
  • Use web.crawl (not crawl_web)

Usage Examples

Research Assistant

code
"Search for recent developments in quantum computing and summarize the key findings"

Content Analysis

code
"Search for competitor pricing pages and extract their pricing tiers"

Code Documentation

code
"Find the official documentation for FastAPI and extract the quickstart guide"

News Monitoring

code
"Search for today's news about artificial intelligence from US sources"

Market Research

code
"Search for customer reviews of iPhone 15 and analyze sentiment"

Pricing

Crawleo MCP uses the same affordable pricing as our API:

  • 10,000 searches → $20
  • 100,000 searches → $100
  • 250,000 searches → $200

Check your usage and manage your subscription at crawleo.dev


Privacy & Security

Zero data retention - We never store your search queries or results
Secure authentication - API keys transmitted over HTTPS
No tracking - Your usage patterns remain private


Support


Links


Is this better? Would you like me to add anything else or create additional guides?

常见问题

io.github.Crawleo/Crawleo-MCP 是什么?

托管版 Crawleo MCP,提供可远程流式访问的 HTTP endpoint,便于集成调用。

相关 Skills

前端设计

by anthropics

Universal
热门

面向组件、页面、海报和 Web 应用开发,按鲜明视觉方向生成可直接落地的前端代码与高质感 UI,适合做 landing page、Dashboard 或美化现有界面,避开千篇一律的 AI 审美。

想把页面做得既能上线又有设计感,就用前端设计:组件到整站都能产出,难得的是能避开千篇一律的 AI 味。

编码与调试
未扫描165.3k

网页应用测试

by anthropics

Universal
热门

用 Playwright 为本地 Web 应用编写自动化测试,支持启动开发服务器、校验前端交互、排查 UI 异常、抓取截图与浏览器日志,适合调试动态页面和回归验证。

借助 Playwright 一站式验证本地 Web 应用前端功能,调 UI 时还能同步查看日志和截图,定位问题更快。

编码与调试
未扫描165.3k

网页构建器

by anthropics

Universal
热门

面向复杂 claude.ai HTML artifact 开发,快速初始化 React + Tailwind CSS + shadcn/ui 项目并打包为单文件 HTML,适合需要状态管理、路由或多组件交互的页面。

在 claude.ai 里做复杂网页 Artifact 很省心,多组件、状态和路由都能顺手搭起来,React、Tailwind 与 shadcn/ui 组合效率高、成品也更精致。

编码与调试
未扫描165.3k

相关 MCP Server

GitHub

编辑精选

by GitHub

热门

GitHub 是 MCP 官方参考服务器,让 Claude 直接读写你的代码仓库和 Issues。

这个参考服务器解决了开发者想让 AI 安全访问 GitHub 数据的问题,适合需要自动化代码审查或 Issue 管理的团队。但注意它只是参考实现,生产环境得自己加固安全。

编码与调试
89.1k

by Context7

热门

Context7 是实时拉取最新文档和代码示例的智能助手,让你告别过时资料。

它能解决开发者查找文档时信息滞后的问题,特别适合快速上手新库或跟进更新。不过,依赖外部源可能导致偶尔的数据延迟,建议结合官方文档使用。

编码与调试
60.0k

by tldraw

热门

tldraw 是让 AI 助手直接在无限画布上绘图和协作的 MCP 服务器。

这解决了 AI 只能输出文本、无法视觉化协作的痛点——想象让 Claude 帮你画流程图或白板讨论。最适合需要快速原型设计或头脑风暴的开发者。不过,目前它只是个基础连接器,你得自己搭建画布应用才能发挥全部潜力。

编码与调试
49.5k

评论