Open-WebSearch

🇨🇳 中文 | 🇺🇸 English

open-websearch provides an MCP server, CLI, and local daemon, and can also be paired with skill-guided agent workflows for live web search and content retrieval without API keys.

Features

• Web search using multi-engine results

  • bing

  • baidu

  • linux.do temporarily unsupported

  • csdn

  • duckduckgo

  • exa

  • brave

  • juejin

  • startpage

• 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

  • github (README files)

  • generic HTTP(S) page / Markdown content

Related MCP server: Web Search MCP Server

Choose the Right Path

• MCP

  • Best when you want to connect open-websearch to Claude Desktop, Cherry Studio, Cursor, or another MCP client.

• CLI

  • Best for one-shot local commands, shell scripts, and direct terminal usage.

• Local daemon

  • Best when you want a reusable long-lived local HTTP service exposing status, GET /health, and POST /search / POST /fetch-*. Start it explicitly with open-websearch serve and check it with open-websearch status.

• Skill

  • Best as an agent-facing guidance layer for setup and usage. A skill does not replace MCP, CLI, or the local daemon; it typically works together with the CLI and/or local daemon to help an agent discover, activate, and use the smallest working path.

Use with a Skill

Install the open-websearch skill for your agent first:

npx skills add https://github.com/Aas-ee/open-webSearch --skill open-websearch

On first use, the skill typically follows this path: detect whether a usable open-websearch path already exists, guide setup/enablement if it does not, validate that the capability is active, and only then continue with search or fetch through the smallest working path.

If the current environment cannot complete setup or activation automatically, you can explicitly have the agent start the local daemon first:

open-websearch serve
open-websearch status

Keep installation proxy settings separate from runtime proxy settings:

• Installation proxy / mirror

  • Use this when the skill or agent is installing open-websearch, playwright, or other npm packages.

  • In restricted networks, npm-specific flags or npm config often work better than generic shell proxy variables, for example:

npm --proxy http://127.0.0.1:7890 --https-proxy http://127.0.0.1:7890 install -g open-websearch

• Runtime proxy

  • Use this when the daemon is already installed and is about to perform live search / fetch work.

  • This affects the open-websearch network traffic after serve starts, for example:

USE_PROXY=true PROXY_URL=http://127.0.0.1:7890 open-websearch serve

If the agent can only get through the package-install step with npm proxy settings, but live search/fetch also needs a proxy after startup, those are two separate configuration steps and should be handled separately.

CLI and Local Daemon

CLI is for one-shot execution. The local daemon is a long-lived local HTTP service for repeated calls with lower startup friction. Use open-websearch serve as the explicit daemon start command and open-websearch status as the explicit daemon status command.

Action commands such as search and fetch-web try the default local daemon first when it is available. If you pass --daemon-url, that daemon path becomes explicit and silent fallback to direct execution is disabled.

Build first:

npm run build

Start the local daemon:

npm run serve
# globally installed: open-websearch serve

Check status:

npm run status -- --json
# globally installed: open-websearch status --json

Run a one-shot local CLI search:

npm run search:cli -- "open web search" --json

Notes:

• Bare open-websearch is the MCP server compatibility entrypoint, not the recommended daemon start command for agent automation.

• For content extraction, prefer searching first and then fetching a more specific result page. Some homepages and JS-heavy landing pages may not expose readable article text through fetch-web.

For the local daemon HTTP API (serve, status, GET /health, POST /search, POST /fetch-*), see docs/http-api.md.

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

• Support for GitHub README fetching (already supported)

Installation Guide

If you are using open-websearch as an MCP server, continue with the MCP-oriented setup below.

NPX Quick Start (Recommended)

The fastest way to get started:

# Basic usage
npx open-websearch@latest

# With environment variables (Linux/macOS)
DEFAULT_SEARCH_ENGINE=duckduckgo ENABLE_CORS=true npx open-websearch@latest

# Windows PowerShell
$env:DEFAULT_SEARCH_ENGINE="duckduckgo"; $env:ENABLE_CORS="true"; npx open-websearch@latest

# Windows CMD
set MODE=stdio && set DEFAULT_SEARCH_ENGINE=duckduckgo && npx open-websearch@latest

# Cross-platform (requires cross-env, Used for local development)
npm install -g open-websearch
npx cross-env DEFAULT_SEARCH_ENGINE=duckduckgo ENABLE_CORS=true open-websearch

Environment Variables:

Common configurations:

# Enable proxy for restricted regions
USE_PROXY=true PROXY_URL=http://127.0.0.1:7890 npx open-websearch@latest

# Only if a target website has a broken certificate chain
FETCH_WEB_INSECURE_TLS=true npx open-websearch@latest

# Request first, then fallback to Playwright if available
SEARCH_MODE=auto npx open-websearch@latest

# Force request-only Bing search
SEARCH_MODE=request npx open-websearch@latest

# Full configuration
DEFAULT_SEARCH_ENGINE=duckduckgo ENABLE_CORS=true USE_PROXY=true PROXY_URL=http://127.0.0.1:7890 PORT=8080 npx open-websearch@latest

Browser-enhanced Bing fallback is opt-in. The published package does not bundle Playwright anymore. Enable it manually with one of these setups:

1. Full local Playwright install:

npm install playwright
npx playwright install chromium
SEARCH_MODE=auto npx open-websearch@latest

2. Reuse an existing browser binary with a slim client:

npm install playwright-core
PLAYWRIGHT_PACKAGE=playwright-core PLAYWRIGHT_EXECUTABLE_PATH=/path/to/chromium SEARCH_MODE=auto npx open-websearch@latest

3. Reuse a Playwright package that already exists elsewhere on the machine:

PLAYWRIGHT_MODULE_PATH=/absolute/path/to/node_modules/playwright SEARCH_MODE=playwright npx open-websearch@latest

4. Connect to an existing remote browser:

npm install playwright-core
PLAYWRIGHT_PACKAGE=playwright-core PLAYWRIGHT_WS_ENDPOINT=ws://127.0.0.1:3000/ SEARCH_MODE=auto npx open-websearch@latest

5. Reuse a local Chrome/Chromium session over CDP:

npm install playwright-core

# Start Chrome/Chromium with a debugging port first
chrome --remote-debugging-port=9222 --user-data-dir=/tmp/open-websearch-chrome

# Then connect through CDP
PLAYWRIGHT_PACKAGE=playwright-core PLAYWRIGHT_CDP_ENDPOINT=http://127.0.0.1:9222 SEARCH_MODE=auto npx open-websearch@latest

This is the most practical setup when you want to reuse your own logged-in or previously verified browser session.

Windows PowerShell example:

npm install playwright-core

& "$env:LOCALAPPDATA\Google\Chrome\Application\chrome.exe" `
  --remote-debugging-port=9222 `
  --user-data-dir="$env:TEMP\open-websearch-chrome"

$env:PLAYWRIGHT_PACKAGE="playwright-core"
$env:PLAYWRIGHT_CDP_ENDPOINT="http://127.0.0.1:9222"
$env:SEARCH_MODE="auto"
npx open-websearch@latest

Mode behavior:

• request: only uses request-based Bing scraping

• auto: tries request first, and only falls back to Playwright when request fails and a manually accessible Playwright client + browser are available

• playwright: forces Playwright and errors if the configured Playwright client or browser target is unavailable

Notes:

• PLAYWRIGHT_MODULE_PATH takes precedence over PLAYWRIGHT_PACKAGE

• PLAYWRIGHT_WS_ENDPOINT takes precedence over PLAYWRIGHT_CDP_ENDPOINT

• Remote endpoints ignore PLAYWRIGHT_EXECUTABLE_PATH and local proxy launch flags

• When Playwright is available, blocked CSDN/Zhihu article fetches and generic web fetches can also retry with browser-acquired cookies

• Without Playwright, fetchWebContent stays on the request-only path. Public pages can still work, but pages that require browser cookies or browser-rendered HTML may fail.

Local Installation

1. Clone or download this repository

2. Install dependencies:

npm install

This installs the core MCP server only. Browser fallback remains optional until you install or connect a Playwright client yourself. 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": {
      "type": "http",
      "url": "http://localhost:3000/mcp"
    },
    "web-search-sse": {
      "type": "sse",
      "url": "http://localhost:3000/sse"
    }
  }
}

NPX Command Line Configuration:

{
  "mcpServers": {
    "web-search": {
      "args": [
        "open-websearch@latest"
      ],
      "command": "npx",
      "env": {
        "MODE": "stdio",
        "DEFAULT_SEARCH_ENGINE": "duckduckgo",
        "ALLOWED_SEARCH_ENGINES": "duckduckgo,bing,exa"
      }
    }
  }
}

Windows NPX configuration:

{
  "mcpServers": {
    "web-search": {
      "command": "cmd",
      "args": [
        "/c",
        "npx",
        "-y",
        "open-websearch@latest"
      ],
      "env": {
        "MODE": "stdio",
        "DEFAULT_SEARCH_ENGINE": "duckduckgo",
        "SYSTEMROOT": "C:/Windows"
      }
    }
  }
}

Proxy and TLS notes:

• open-websearch now disables Axios environment-proxy auto-detection internally and only uses the explicit USE_PROXY + PROXY_URL path.

• When USE_PROXY=true, all Axios-based network requests follow the configured PROXY_URL path instead of mixing direct requests with environment-proxy behavior.

• If PROXY_URL points to a local rule-based proxy client, that client can still decide which destinations go DIRECT and which ones are proxied.

• If PROXY_URL points to a fixed upstream proxy or overseas egress, region-sensitive sites such as Baidu, CSDN, Juejin, Linux.do, or GitHub may behave differently than before.

• If your host machine already sets HTTP_PROXY or HTTPS_PROXY, they will no longer override the server's internal request behavior.

• Prefer configuring NODE_EXTRA_CA_CERTS on Windows when a site has a missing intermediate CA.

• Use FETCH_WEB_INSECURE_TLS=true only as a last resort for fetchWebContent, since it weakens TLS verification.

Local STDIO Configuration for Cherry Studio (Windows):

{
  "mcpServers": {
    "open-websearch-local": {
      "command": "node",
      "args": ["C:/path/to/your/project/build/index.js"],
      "env": {
        "MODE": "stdio",
        "DEFAULT_SEARCH_ENGINE": "duckduckgo",
        "ALLOWED_SEARCH_ENGINES": "duckduckgo,bing,exa"
      }
    }
  }
}

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:

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 six tools: search, fetchLinuxDoArticle, fetchCsdnArticle, fetchGithubReadme, fetchJuejinArticle, and fetchWebContent.

For the local daemon HTTP API (serve, status, GET /health, POST /search, POST /fetch-*), see docs/http-api.md.

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,juejin,startpage) default runtime-configured engine
  "searchMode": string    // Optional: request, auto, or playwright (currently only affects 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", "juejin"] // 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"
  }
]

fetchGithubReadme Tool Usage

Used to fetch README content from GitHub repositories.

{
  "url": string    // GitHub repository URL (supports HTTPS, SSH formats)
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "fetchGithubReadme",
  arguments: {
    url: "https://github.com/Aas-ee/open-webSearch"
  }
})

Supported URL formats:

• HTTPS: https://github.com/owner/repo

• HTTPS with .git: https://github.com/owner/repo.git

• SSH: git@github.com:owner/repo.git

• URLs with parameters: https://github.com/owner/repo?tab=readme

Response example:

[
  {
    "content": "<div align=\"center\">\n\n# Open-WebSearch MCP Server..."
  }
]

fetchWebContent Tool Usage

Fetch content directly from public HTTP(S) links, including Markdown files (.md) and ordinary web pages.

{
  "url": string,         // Public HTTP(S) URL
  "maxChars": number     // Optional: max returned content length (1000-200000, default 30000)
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "fetchWebContent",
  arguments: {
    url: "https://raw.githubusercontent.com/Aas-ee/open-webSearch/main/README.md",
    maxChars: 12000
  }
})

Response example:

{
  "url": "https://raw.githubusercontent.com/Aas-ee/open-webSearch/main/README.md",
  "finalUrl": "https://raw.githubusercontent.com/Aas-ee/open-webSearch/main/README.md",
  "contentType": "text/plain; charset=utf-8",
  "title": "",
  "truncated": false,
  "content": "# Open-WebSearch MCP Server ..."
}

fetchJuejinArticle Tool Usage

Used to fetch complete content of Juejin articles.

{
  "url": string    // Juejin article URL from search results
}

Usage example:

use_mcp_tool({
  server_name: "web-search",
  tool_name: "fetchJuejinArticle",
  arguments: {
    url: "https://juejin.cn/post/7520959840199360563"
  }
})

Supported URL format:

• https://juejin.cn/post/{article_id}

Response example:

[
  {
    "content": "🚀 开源 AI 联网搜索工具：Open-WebSearch MCP 全新升级，支持多引擎 + 流式响应..."
  }
]

Usage Limitations

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

1. 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

2. 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

3. 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

4. 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

5. 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:

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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