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Ddg Search
What is Ddg Search
ddg_search is a powerful Model Context Protocol (MCP) server designed for web search and URL content extraction using DuckDuckGo, emphasizing speed and privacy.
Use cases
Use cases include integrating with AI assistants for enhanced search capabilities, extracting metadata for SEO analysis, and performing web scraping for research purposes.
How to use
To use ddg_search, you can run it instantly with npx by executing ‘npx -y @oevortex/ddg_search’ in your terminal. Alternatively, it can be installed globally using npm.
Key features
Key features include web search using DuckDuckGo HTML, URL content extraction with smart filtering, URL metadata extraction (title, description, images), performance optimization with caching, security features like rate limiting and rotating user agents, MCP compliance, and no API keys required.
Where to use
ddg_search can be used in various fields such as web development, data analysis, and AI applications where web search and content extraction are needed.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Ddg Search
ddg_search is a powerful Model Context Protocol (MCP) server designed for web search and URL content extraction using DuckDuckGo, emphasizing speed and privacy.
Use cases
Use cases include integrating with AI assistants for enhanced search capabilities, extracting metadata for SEO analysis, and performing web scraping for research purposes.
How to use
To use ddg_search, you can run it instantly with npx by executing ‘npx -y @oevortex/ddg_search’ in your terminal. Alternatively, it can be installed globally using npm.
Key features
Key features include web search using DuckDuckGo HTML, URL content extraction with smart filtering, URL metadata extraction (title, description, images), performance optimization with caching, security features like rate limiting and rotating user agents, MCP compliance, and no API keys required.
Where to use
ddg_search can be used in various fields such as web development, data analysis, and AI applications where web search and content extraction are needed.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
DuckDuckGo & Felo AI Search MCP 🔍🧠
A blazing-fast, privacy-friendly Model Context Protocol (MCP) server for web search and AI-powered responses using DuckDuckGo and Felo AI.
[!IMPORTANT]
DuckDuckGo Search MCP supports the Model Context Protocol (MCP) standard, making it compatible with various AI assistants and tools.
✨ Features
[!IMPORTANT]
Unlike many search tools, this package performs actual web scraping rather than using limited APIs, giving you more comprehensive results.
🚀 Quick Start
npx -y @oevortex/ddg_search@latest
[!TIP]
This will download and run the latest version of the MCP server directly without installation – perfect for quick use with AI assistants.
🛠️ Installation Options
Global Installation
npm install -g @oevortex/ddg_search
Run globally:
ddg-search-mcp
Local Installation (Development)
git clone https://github.com/OEvortex/ddg_search.git
cd ddg_search
npm install
npm start
🧑💻 Command Line Options
npx -y @oevortex/ddg_search@latest --help
[!TIP]
Use the–versionflag to check which version you’re running.
🤖 Using with MCP Clients
[!IMPORTANT]
The most common way to use this tool is by integrating it with MCP-compatible AI assistants.
Add the server to your MCP client configuration:
{
"mcpServers": {
"ddg-search": {
"command": "npx",
"args": [
"-y",
"@oevortex/ddg_search@latest"
]
}
}
}
Or if installed globally:
{
"mcpServers": {
"ddg-search": {
"command": "ddg-search-mcp"
}
}
}
[!TIP]
After configuring, restart your MCP client to apply the changes.
🧰 Tools Overview
web-search- query (string, required): The search query
- page (integer, optional, default: 1): Page number
- numResults (integer, optional, default: 10): Number of results (1-20)
felo-search- query (string, required): The search query or prompt
- stream (boolean, optional, default: false): Whether to stream the response
fetch-url- url (string, required): The URL to fetch
- maxLength (integer, optional, default: 10000): Max content length
- extractMainContent (boolean, optional, default: true): Extract main content
- includeLinks (boolean, optional, default: true): Include link text
- includeImages (boolean, optional, default: true): Include image alt text
- excludeTags (array, optional): Tags to exclude
url-metadata- url (string, required): The URL to extract metadata from
📁 Project Structure
bin/ # Command-line interface src/ index.js # Main entry point tools/ # Tool definitions and handlers searchTool.js fetchUrlTool.js metadataTool.js feloTool.js utils/ search.js # Search and URL utilities search_felo.js # Felo AI search utilities package.json README.md
🤝 Contributing
Contributions are welcome! Please open issues or submit pull requests.
[!NOTE]
Please follow the existing code style and add tests for new features.
📺 YouTube Channel
📄 License
Apache License 2.0
[!NOTE]
This project is licensed under the Apache License 2.0 – see the LICENSE file for details.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










