web-browser-mcp-server
✨ 特点
🌐 使 AI 助手能够通过简单的 MCP 界面浏览和提取网络上的内容。
Web 浏览器 MCP 服务器通过消息控制协议 (MCP) 为 AI 模型提供浏览网站、提取内容和理解网页的能力。它支持使用 CSS 选择器进行智能内容提取,并具备强大的错误处理功能。
Related MCP server: mcp-web-tools
✨ 核心功能
🎯智能内容提取:使用 CSS 选择器准确定位您需要的内容
⚡闪电般快速:采用异步处理构建,以实现最佳性能
📊丰富的元数据:捕获标题、链接和结构化内容
🛡️强大且可靠:内置错误处理和超时管理
🌍跨平台:可在 Python 运行的任何地方使用
🚀 快速入门
通过 Smithery 安装
要通过Smithery自动安装 Claude Desktop 的 Web 浏览器服务器:
npx -y @smithery/cli install web-browser-mcp-server --client claude手动安装
使用 uv 安装:
uv tool install web-browser-mcp-server对于开发:
# Clone and set up development environment
git clone https://github.com/blazickjp/web-browser-mcp-server.git
cd web-browser-mcp-server
# Create and activate virtual environment
uv venv
source .venv/bin/activate
# Install with test dependencies
uv pip install -e ".[test]"🔌 MCP 集成
将此配置添加到您的 MCP 客户端配置文件中:
{
"mcpServers": {
"web-browser-mcp-server": {
"command": "uv",
"args": [
"tool",
"run",
"web-browser-mcp-server"
],
"env": {
"REQUEST_TIMEOUT": "30"
}
}
}
}对于开发:
{
"mcpServers": {
"web-browser-mcp-server": {
"command": "uv",
"args": [
"--directory",
"path/to/cloned/web-browser-mcp-server",
"run",
"web-browser-mcp-server"
],
"env": {
"REQUEST_TIMEOUT": "30"
}
}
}
}💡 可用工具
服务器提供了强大的网页浏览工具:
浏览网页
使用可选的 CSS 选择器浏览网页并提取内容:
# Basic webpage fetch
result = await call_tool("browse_webpage", {
"url": "https://example.com"
})
# Target specific content with CSS selectors
result = await call_tool("browse_webpage", {
"url": "https://example.com",
"selectors": {
"headlines": "h1, h2",
"main_content": "article.content",
"navigation": "nav a"
}
})⚙️ 配置
通过环境变量配置:
多变的 | 目的 | 默认 |
| 网页请求超时(秒) | 三十 |
🧪 测试
运行测试套件:
python -m pytest📄 许可证
根据 MIT 许可证发布。详情请参阅许可证文件。
由 Pear Labs 团队倾情打造
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