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cloudflare-browser-rendering

一个利用 Cloudflare 浏览器渲染来提取和处理网页内容以供大型语言模型(LLMs)作为上下文使用的服务器,提供抓取页面、搜索文档、提取结构化内容和总结内容的工具。

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README

Cloudflare Browser Rendering Experiments & MCP Server

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.

Web Content Server MCP server

Project Structure

cloudflare-browser-rendering/
├── examples/                   # Example implementations and utilities
│   ├── basic-worker-example.js # Basic Worker with Browser Rendering
│   ├── minimal-worker-example.js # Minimal implementation
│   ├── debugging-tools/        # Tools for debugging
│   │   └── debug-test.js       # Debug test utility
│   └── testing/                # Testing utilities
│       └── content-test.js     # Content testing utility
├── experiments/                # Educational experiments
│   ├── basic-rest-api/         # REST API tests
│   ├── puppeteer-binding/      # Workers Binding API tests
│   └── content-extraction/     # Content processing tests
├── src/                        # MCP server source code
│   ├── index.ts                # Main entry point
│   ├── server.ts               # MCP server implementation
│   ├── browser-client.ts       # Browser Rendering client
│   └── content-processor.ts    # Content processing utilities
├── puppeteer-worker.js         # Cloudflare Worker with Browser Rendering binding
├── test-puppeteer.js           # Tests for the main implementation
├── wrangler.toml               # Wrangler configuration for the Worker
├── cline_mcp_settings.json.example # Example MCP settings for Cline
├── .gitignore                  # Git ignore file
└── LICENSE                     # MIT License

Prerequisites

  • Node.js (v16 or later)
  • A Cloudflare account with Browser Rendering enabled
  • TypeScript
  • Wrangler CLI (for deploying the Worker)

Installation

  1. Clone the repository:
git clone https://github.com/yourusername/cloudflare-browser-rendering.git
cd cloudflare-browser-rendering
  1. Install dependencies:
npm install

Cloudflare Worker Setup

  1. Install the Cloudflare Puppeteer package:
npm install @cloudflare/puppeteer
  1. Configure Wrangler:
# wrangler.toml
name = "browser-rendering-api"
main = "puppeteer-worker.js"
compatibility_date = "2023-10-30"
compatibility_flags = ["nodejs_compat"]

[browser]
binding = "browser"
  1. Deploy the Worker:
npx wrangler deploy
  1. Test the Worker:
node test-puppeteer.js

Running the Experiments

Basic REST API Experiment

This experiment demonstrates how to use the Cloudflare Browser Rendering REST API to fetch and process web content:

npm run experiment:rest

Puppeteer Binding API Experiment

This experiment demonstrates how to use the Cloudflare Browser Rendering Workers Binding API with Puppeteer for more advanced browser automation:

npm run experiment:puppeteer

Content Extraction Experiment

This experiment demonstrates how to extract and process web content specifically for use as context in LLMs:

npm run experiment:content

MCP Server

The MCP server provides tools for fetching and processing web content using Cloudflare Browser Rendering for use as context in LLMs.

Building the MCP Server

npm run build

Running the MCP Server

npm start

Or, for development:

npm run dev

MCP Server Tools

The MCP server provides the following tools:

  1. fetch_page - Fetches and processes a web page for LLM context
  2. search_documentation - Searches Cloudflare documentation and returns relevant content
  3. extract_structured_content - Extracts structured content from a web page using CSS selectors
  4. summarize_content - Summarizes web content for more concise LLM context

Configuration

To use your Cloudflare Browser Rendering endpoint, set the BROWSER_RENDERING_API environment variable:

export BROWSER_RENDERING_API=https://YOUR_WORKER_URL_HERE

Replace YOUR_WORKER_URL_HERE with the URL of your deployed Cloudflare Worker. You'll need to replace this placeholder in several files:

  1. In test files: test-puppeteer.js, examples/debugging-tools/debug-test.js, examples/testing/content-test.js
  2. In the MCP server configuration: cline_mcp_settings.json.example
  3. In the browser client: src/browser-client.ts (as a fallback if the environment variable is not set)

Integrating with Cline

To integrate the MCP server with Cline, copy the cline_mcp_settings.json.example file to the appropriate location:

cp cline_mcp_settings.json.example ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

Or add the configuration to your existing cline_mcp_settings.json file.

Key Learnings

  1. Cloudflare Browser Rendering requires the @cloudflare/puppeteer package to interact with the browser binding.
  2. The correct pattern for using the browser binding is:
    import puppeteer from '@cloudflare/puppeteer';
    
    // Then in your handler:
    const browser = await puppeteer.launch(env.browser);
    const page = await browser.newPage();
    
  3. When deploying a Worker that uses the Browser Rendering binding, you need to enable the nodejs_compat compatibility flag.
  4. Always close the browser after use to avoid resource leaks.

License

MIT

help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client