Open Websearch

🚀 Open-WebSearch MCP Server

A Model Context Protocol (MCP) server based on multi-engine search results, supporting free web search without API keys.

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🚀 Quick Start

The Open-WebSearch MCP Server is a powerful tool that offers free web search without API keys, leveraging multi-engine search results. You can quickly get it up and running through local installation or Docker deployment.

✨ Features

• Multi-engine Web Search: Utilize multiple search engines including Bing, Baidu, CSDN, DuckDuckGo, Exa, and Brave to conduct web searches. Note that Linux.do is temporarily unsupported.
• HTTP Proxy Support: Configure an HTTP proxy to access restricted resources.
• No API Keys Required: Conduct searches without the need for API keys or authentication.
• Structured Results: Receive search results with structured information such as titles, URLs, and descriptions.
• Configurable Results: Customize the number of search results per query.
• Customizable Default Engine: Set your preferred default search engine.
• Article Content Fetching: Support for fetching individual article content, especially from CSDN.

📦 Installation

Local Installation

1. Clone or download this repository.
2. Install dependencies:

npm install

3. Build the server:

npm run build

4. Add the server to your MCP configuration:

Cherry Studio:

{
  "mcpServers": {
    "web-search": {
      "name": "Web Search MCP",
      "type": "streamableHttp",
      "description": "Multi-engine web search with article fetching",
      "isActive": true,
      "baseUrl": "http://localhost:3000/mcp"
    }
  }
}

VSCode (Claude Dev Extension):

{
  "mcpServers": {
    "web-search": {
      "transport": {
        "type": "streamableHttp",
        "url": "http://localhost:3000/mcp"
      }
    },
    "web-search-sse": {
      "transport": {
        "type": "sse",
        "url": "http://localhost:3000/sse"
      }
    }
  }
}

Claude Desktop:

{
  "mcpServers": {
    "web-search": {
      "transport": {
        "type": "streamableHttp",
        "url": "http://localhost:3000/mcp"
      }
    },
    "web-search-sse": {
      "transport": {
        "type": "sse",
        "url": "http://localhost:3000/sse"
      }
    }
  }
}

Docker Deployment

Quick deployment using Docker Compose:

docker-compose up -d

Or use Docker directly:

docker run -d --name web-search -p 3000:3000 -e ENABLE_CORS=true -e CORS_ORIGIN=* ghcr.io/aas-ee/open-web-search:latest

Environment variable configuration:

# Enable CORS (default: false)
ENABLE_CORS=true

# CORS origin configuration (default: *)
CORS_ORIGIN=*

# Default search engine (options: bing, duckduckgo, exa, brave, default: bing)
DEFAULT_SEARCH_ENGINE=duckduckgo

# Enable HTTP proxy (default: false)
USE_PROXY=true

# Proxy server URL (default: http://127.0.0.1:10809)
PROXY_URL=http://your-proxy-server:port

# Server port (default: 3000)
PORT=8080

Then configure in your MCP client:

{
  "mcpServers": {
    "web-search": {
      "name": "Web Search MCP",
      "type": "streamableHttp",
      "description": "Multi-engine web search with article fetching",
      "isActive": true,
      "baseUrl": "http://localhost:3000/mcp"
    },
    "web-search-sse": {
      "transport": {
        "name": "Web Search MCP",
        "type": "sse",
        "description": "Multi-engine web search with article fetching",
        "isActive": true,
        "url": "http://localhost:3000/sse"
      }
    }
  }
}

💻 Usage Examples

The server provides three tools: search, fetchLinuxDoArticle, and fetchCsdnArticle.

Basic Usage - search Tool

{
  "query": string,        // Search query
  "limit": number,        // Optional: Number of results to return (default: 10)
  "engines": string[]     // Optional: Engines to use (bing,baidu,linuxdo,csdn,duckduckgo,exa,brave) default bing
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "search",
  arguments: {
    query: "search content",
    limit: 3,  // Optional parameter
    engines: ["bing", "csdn", "duckduckgo", "exa", "brave"] // Optional parameter, supports multi-engine combined search
  }
})

Response example:

[
  {
    "title": "Example Search Result",
    "url": "https://example.com",
    "description": "Description text of the search result...",
    "source": "Source",
    "engine": "Engine used"
  }
]

Advanced Usage - fetchCsdnArticle Tool

Used to fetch complete content of CSDN blog articles.

{
  "url": string    // URL from CSDN search results using the search tool
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "fetchCsdnArticle",
  arguments: {
    url: "https://blog.csdn.net/xxx/article/details/xxx"
  }
})

Response example:

[
  {
    "content": "Example search result"
  }
]

Advanced Usage - fetchLinuxDoArticle Tool

Used to fetch complete content of Linux.do forum articles.

{
  "url": string    // URL from linuxdo search results using the search tool
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "fetchLinuxDoArticle",
  arguments: {
    url: "https://xxxx.json"
  }
})

Response example:

[
  {
    "content": "Example search result"
  }
]

📚 Documentation

Usage Limitations

Since this tool works by scraping multi-engine search results, please note the following important limitations:

⚠️ Important Note

• Rate Limiting: Too many searches in a short time may cause the used engines to temporarily block requests. Recommendations include maintaining reasonable search frequency, using the limit parameter judiciously, and adding delays between searches when necessary.
• Result Accuracy: Depends on the HTML structure of corresponding engines, may fail when engines update. Some results may lack metadata like descriptions, and complex search operators may not work as expected.
• Legal Terms: This tool is for personal use only. Please comply with the terms of service of corresponding engines and implement appropriate rate limiting based on your actual use case.
• Search Engine Configuration: The default search engine can be set via the DEFAULT_SEARCH_ENGINE environment variable. Supported engines are bing, duckduckgo, exa, brave. The default engine is used when searching specific websites.
• Proxy Configuration: An HTTP proxy can be configured when certain search engines are unavailable in specific regions. Enable proxy with environment variable USE_PROXY=true and configure proxy server address with PROXY_URL.

Contributing

Welcome to submit issue reports and feature improvement suggestions!

Contributor Guide

If you want to fork this repository and publish your own Docker image, you need to make the following configurations:

GitHub Secrets Configuration

To enable automatic Docker image building and publishing, please add the following secrets in your GitHub repository settings (Settings → Secrets and variables → Actions):

Required Secrets:

• GITHUB_TOKEN: Automatically provided by GitHub (no setup needed)

Optional Secrets (for Alibaba Cloud ACR):

• ACR_REGISTRY: Your Alibaba Cloud Container Registry URL (e.g., registry.cn-hangzhou.aliyuncs.com)
• ACR_USERNAME: Your Alibaba Cloud ACR username
• ACR_PASSWORD: Your Alibaba Cloud ACR password
• ACR_IMAGE_NAME: Your image name in ACR (e.g., your-namespace/open-web-search)

CI/CD Workflow

The repository includes a GitHub Actions workflow (.github/workflows/docker.yml) that automatically:

1. Trigger Conditions:
   • Push to main branch
   • Push version tags (v*)
   • Manual workflow trigger
2. Build and Push to:
   • GitHub Container Registry (ghcr.io) - always enabled
   • Alibaba Cloud Container Registry - only enabled when ACR secrets are configured
3. Image Tags:
   • ghcr.io/your-username/open-web-search:latest
   • your-acr-address/your-image-name:latest (if ACR is configured)

Fork and Publish Steps:

1. Fork the repository to your GitHub account.
2. Configure secrets (if you need ACR publishing):
   • Go to Settings → Secrets and variables → Actions in your forked repository.
   • Add the ACR-related secrets listed above.
3. Push changes to the main branch or create version tags.
4. GitHub Actions will automatically build and push your Docker image.
5. Use your image, update the Docker command:

docker run -d --name web-search -p 3000:3000 -e ENABLE_CORS=true -e CORS_ORIGIN=* ghcr.io/your-username/open-web-search:latest

Notes:

• If you don't configure ACR secrets, the workflow will only publish to GitHub Container Registry.
• Make sure your GitHub repository has Actions enabled.
• The workflow will use your GitHub username (converted to lowercase) as the GHCR image name.

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