Open-WebSearch MCP Server

中文

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

Features

Web search using multi-engine results
- bing
- baidu
- ~~linux.do~~ temporarily unsupported
- csdn
- duckduckgo
- exa
- brave
HTTP proxy configuration support for accessing restricted resources
No API keys or authentication required
Returns structured results with titles, URLs, and descriptions
Configurable number of results per search
Customizable default search engine
Support for fetching individual article content
- csdn

TODO

Support for ~~Bing~~ (already supported), ~~DuckDuckGo~~ (already supported), ~~Exa~~ (already supported), ~~Brave~~ (already supported), Google and other search engines
Support for more blogs, forums, and social platforms
Optimize article content extraction, add support for more sites

Installation Guide

Local Installation

Clone or download this repository
Install dependencies:

npm install

Build the server:

npm run build

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

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 Guide

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

search Tool Usage

{
  "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"
  }
]

fetchCsdnArticle Tool Usage

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"
  }
]

fetchLinuxDoArticle Tool Usage

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"
  }
]

Usage Limitations

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

Rate Limiting:
- Too many searches in a short time may cause the used engines to temporarily block requests
- Recommendations:
  - Maintain reasonable search frequency
  - Use the limit parameter judiciously
  - Add 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
- 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
- Implement appropriate rate limiting based on your actual use case
Search Engine Configuration:
- Default search engine can be set via the DEFAULT_SEARCH_ENGINE environment variable
- Supported engines: bing, duckduckgo, exa, brave
- The default engine is used when searching specific websites
Proxy Configuration:
- HTTP proxy can be configured when certain search engines are unavailable in specific regions
- Enable proxy with environment variable USE_PROXY=true
- 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:

Trigger Conditions:
- Push to main branch
- Push version tags (v*)
- Manual workflow trigger
Build and Push to:
- GitHub Container Registry (ghcr.io) - always enabled
- Alibaba Cloud Container Registry - only enabled when ACR secrets are configured
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:

Fork the repository to your GitHub account
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
Push changes to the main branch or create version tags
GitHub Actions will automatically build and push your Docker image

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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Open-WebSearch MCP Server