What prerequisites are needed?
Node.js v16 or later, a Cloudflare account with Browser Rendering enabled, TypeScript, and the Wrangler CLI.
@amotivv
基本信息
This project demonstrates how to use Cloudflare Browser Rendering to extract web content for LLM context. It includes experiments with the REST API and Workers Binding API, as well as an MCP server implementation that can be used to provide web context to LLMs.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"cloudflare-browser-rendering": {
"command": "npx",
"args": [
"wrangler",
"deploy"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
This project demonstrates how to use Cloudflare Browser Rendering to extract web content for LLM context. It includes experiments with the REST API and Workers Binding API, as well as an MCP server implementation that provides web context to LLMs via tools like fetching pages and summarizing content.
Clone the repository, install dependencies, and configure a Cloudflare Worker with the Browser Rendering binding and the nodejs_compat flag. Deploy the Worker, set the BROWSER_RENDERING_API environment variable to your Worker’s URL, then build and run the MCP server with npm run build and npm start. The MCP server exposes tools that can be invoked through compatible clients (e.g., Cline via MCP settings).
Node.js v16 or later, a Cloudflare account with Browser Rendering enabled, TypeScript, and the Wrangler CLI.
Set up `wrangler.toml` with a `[browser]` binding (e.g., `binding = "browser"`), enable `nodejs_compat`, then deploy with `npx wrangler deploy`.
Set the `BROWSER_RENDERING_API` environment variable to the URL of your deployed Cloudflare Worker.
The MCP server provides `fetch_page`, `search_documentation`, `extract_structured_content`, and `summarize_content`.
Use the `@cloudflare/puppeteer` package, launch the browser with `puppeteer.launch(env.browser)`, enable the `nodejs_compat` compatibility flag, and always close the
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