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MCPMonkey服务器

MCPMonkey是Violentmonkey的分支,增强其功能以支持模型上下文协议(MCP)服务器,弥合AI与浏览器交互差距。它提供标签页管理等浏览器交互功能,兼容用户脚本,未来还将增加MCP服务器管理等,适用于开发者和普通用户。

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README

MCPMonkey

MCPMonkey is a fork of Violentmonkey, extending its powerful userscript capabilities to support Model Context Protocol (MCP) servers. This project aims to bridge the gap between AI language models and browser interactions.

About MCPMonkey

MCPMonkey enhances the browser extension capabilities of Violentmonkey to provide a user-friendly interface for managing and using Model Context Protocol (MCP) servers. This allows AI language models like those used in Cursor to interact with your browser in meaningful ways.

Current Features

MCPMonkey currently implements these key features:

  • Tab Management (browserAction Tool):

    • Get information about all open tabs
    • Create new tabs
    • Close tabs
    • Activate (focus) tabs
    • Duplicate tabs
  • Page Style Extraction (getPageStyles Tool):

    • Extract styling information from web pages for AI analysis
    • Returns structured JSON data about styles
    • Includes global styles, computed styles, color schemes, typography
  • User Script Support: Full compatibility with existing userscripts (inherited from Violentmonkey)

Planned Features

The following features are planned for future development:

  • MCP Server Management: Install and manage multiple MCP servers directly from your browser
  • Enhanced Browser Access: Allow AI tools to interact with:
    • Browsing history
    • Bookmarks
    • Dev console logs
    • Other installed extensions
  • Permissions Control: Fine-grained control over what resources each MCP server can access
  • Community Hub: Share and discover MCP servers and scripts

Cursor MCP Integration

MCPMonkey consists of two main components that need to be installed in the following order:

  1. MCP Server
  2. Browser Extension

1. Adding the MCP Server to Cursor

Using the published NPM package:

  • In Cursor, go to Settings > Features > MCP Servers
  • Click the + Add New MCP Server button
  • Configure the connection with:
    • Name: mcpmonkey-server
    • Type: command
    • Command: npx mcpmonkey-server

Or if building yourself:

# Navigate to the server directory
cd mcpmonkey-server

# Install dependencies
yarn

# Build the server
yarn build

# Run the server
node build/index.js
  • Configuring in Cursor:
    • Name: mcpmonkey-server
    • Type: command
    • Command: node /absolute/path/to/mcpmonkey-server/build/index.js

Cursor connects to the MCPMonkey server using the stdio transport for MCP communication. Once configured, Cursor's Agent in Composer will automatically use available MCP tools when relevant.

Note: in Cursor 0.46+ MCP settings are in their own tab and there is support for .cursor/mcp.json files. More here.

2. Browser Extension Installation

Firefox Installation

  1. Build the project following the Development instructions below
  2. Open Firefox and navigate to about:debugging
  3. Click "This Firefox" in the left sidebar
  4. Click "Load Temporary Add-on..."
  5. Navigate to the dist folder in your MCPMonkey build directory
  6. Select any file from the dist folder to load the extension

Note: As this is a temporary installation, you'll need to reload the extension each time you restart Firefox.

We plan on offering .xpi files soon.

MCPMonkey's Browser Tools

Our implementation of MCP tools provides AI language models like those in Cursor with powerful browser interaction capabilities:

  • browserAction Tool:

    • Get information about all open tabs
    • Create new tabs
    • Close tabs
    • Activate (focus) tabs
    • Duplicate tabs
  • getPageStyles Tool:

    • Extract page styling information (global styles, computed styles, color schemes, typography)
    • Returns structured JSON data for AI analysis
    • Uses content script bridge for communication with web pages

These tools allow AI models to have meaningful, context-aware interactions with your browsing session through a WebSocket connection on port 3025.

For development and testing, you can run the server with the MCP inspector:

# Run with MCP inspector for debugging
npx @modelcontextprotocol/inspector node build/index.js

The server implements both stdio and WebSocket interfaces, with the WebSocket server running on port 3025 for internal communication with the browser extension.

Use Cases

  • For Developers:

    • Access browser resources directly from Cursor or other AI tools
    • View console logs and debug information in your AI development environment
    • Create custom MCP servers for specific development needs
  • For Users:

    • Let your desktop chatbot help you find that website you visited last week
    • Allow AI tools to draft social media messages or emails
    • Automate browser interactions through natural language commands

Development

Extension Development

Install Node.js and Yarn v1.x.
The version of Node.js should match "node" key in package.json.

# Install dependencies
$ yarn

# Watch and compile
$ yarn build

Then load the extension from 'dist/'.

Technical Details

Currently implemented technical components:

  • WebSocket Communication: The extension and server communicate internally via WebSocket on port 3025
  • Content Script Bridge: Allows for interaction with web page content through secure messaging
  • Zod Schema Validation: Ensures data integrity between components with runtime type checking
  • Stdio Transport: External MCP clients like Cursor connect via stdio transport

Credits

This project is based on Violentmonkey, an excellent userscript manager that provides the foundation for MCPMonkey's enhanced capabilities. We extend our gratitude to the Violentmonkey team and contributors for their outstanding work.

Community

https://mcpmonkey.com - For more documentation and MCP tool scripts

License

This project is licensed under the same terms as Violentmonkey. See the LICENSE file for details.

We may add paid features in the future.

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载,用户一般按页面提供的连接方式或授权流程接入,不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖,把 server_config 复制到 MCP 客户端,并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端