Cloudflare Browser Rendering
About
Integrates with Cloudflare's Browser Rendering API to enable web scraping and screenshot capture using Puppeteer for dynamic content processing and automated visual testing.
Details
- Repository
- amotivv/cloudflare-browser-rendering
- Transport
- SSE
- License
- MIT
Explore
- Demonstrates Cloudflare Browser Rendering for LLM context
- Includes REST API and Workers Binding API experiments
- Provides an MCP server with four tools
- Tools: fetch_page, search_documentation, extract_structured_content, summarize_content
- Integrates with Cline via MCP settings
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Cloudflare Browser RenderingCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Node.js (v16 or later)
- A Cloudflare account with Browser Rendering enabled
- TypeScript
- Wrangler CLI (for deploying the Worker)
1. Install the Cloudflare Puppeteer package:
npm install @cloudflare/puppeteer
2. Configure Wrangler:
bash
npm start
Or, for development:
bashnpm run dev
```
fetch_page
Fetches and processes a web page for LLM context.
search_documentation
Searches Cloudflare documentation and returns relevant content.
extract_structured_content
Extracts structured content from a web page using CSS selectors.
summarize_content
Summarizes web content for more concise LLM context.
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
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"cloudflare browser rendering": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}
Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}
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.
<a href="https://glama.ai/mcp/servers/wg9fikq571">
</a>
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
2. Install dependencies:
npm install
Cloudflare Worker Setup
1. Install the Cloudflare Puppeteer package:
npm install @cloudflare/puppeteer
2. Configure Wrangler:
```toml
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