Ubersuggest MCP Server
An MCP server that integrates Neil Patel's Ubersuggest SEO platform with Cursor IDE, enabling AI-assisted SEO analysis directly within your development environment.
Tools
ubersuggest_domain_overview
Get comprehensive domain analysis including traffic and ranking data
ubersuggest_keyword_research
Research keywords with volume, difficulty, and competition data
ubersuggest_site_audit
Perform comprehensive site audit for technical SEO issues
ubersuggest_traffic_estimation
Estimate organic traffic potential for a domain
README
Ubersuggest MCP Server
An MCP (Model Context Protocol) server that integrates Neil Patel's Ubersuggest SEO platform with Cursor IDE, enabling AI-assisted SEO analysis directly within your development environment.
Features
- Domain Overview: Comprehensive domain analysis including traffic and ranking data
- Keyword Research: Research keywords with volume, difficulty, and competition metrics
- Site Audit: Perform technical SEO audits to identify optimization opportunities
- Traffic Estimation: Estimate organic traffic potential for domains
Prerequisites
- Node.js v16 or higher
- Ubersuggest account credentials
- Cursor IDE with MCP support
Installation
- Clone the repository:
git clone https://github.com/yourusername/mcp-ubersuggest.git
cd mcp-ubersuggest
- Install dependencies:
npm install
- Create a
.envfile based on.env.example:
cp .env.example .env
- Add your Ubersuggest credentials to
.env:
UBERSUGGEST_USERNAME=your-email@example.com
UBERSUGGEST_PASSWORD=your-password
Usage
Running the MCP Server
npm start
For development with auto-reload:
npm run dev
Configuring Cursor IDE
Add the following to your Cursor IDE's MCP configuration:
{
"mcpServers": {
"ubersuggest-seo": {
"command": "node",
"args": ["/path/to/mcp-ubersuggest/src/index.js"],
"env": {
"UBERSUGGEST_USERNAME": "your-email@example.com",
"UBERSUGGEST_PASSWORD": "your-password"
}
}
}
}
Available Tools
1. Domain Overview
ubersuggest_domain_overview
- Analyzes domain performance metrics
- Parameters: domain (required), country (optional)
2. Keyword Research
ubersuggest_keyword_research
- Researches keywords with detailed metrics
- Parameters: keyword (required), language (optional), location (optional)
3. Site Audit
ubersuggest_site_audit
- Performs technical SEO audit
- Parameters: url (required), pages_limit (optional)
4. Traffic Estimation
ubersuggest_traffic_estimation
- Estimates organic traffic potential
- Parameters: domain (required), period (optional)
Legal Notice
⚠️ IMPORTANT: This is an unofficial integration that uses reverse-engineered endpoints. Using this tool may violate Ubersuggest's Terms of Service. Users are responsible for:
- Reviewing and complying with Ubersuggest's Terms of Service
- Understanding the legal risks of web scraping
- Using conservative rate limits to minimize server impact
- Accepting all risks associated with using this unofficial integration
Security Considerations
- Credentials are stored in environment variables
- All API communications use HTTPS
- Rate limiting is implemented to prevent detection
- Session tokens are managed securely
Contributing
Contributions are welcome! Please read our contributing guidelines before submitting PRs.
License
MIT License - see LICENSE file for details
Support
For issues and questions, please use the GitHub issue tracker.
Disclaimer
This project is not affiliated with, endorsed by, or sponsored by Neil Patel or Ubersuggest. Use at your own risk.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。