opentiny/webmcp-sdk

Última actividad de origen registrada: 14 de octubre de 2026 a las 02:25

Catálogo de SkillsMP actualizado: 9 de noviembre de 2026 a las 14:22

skills recopiladas: 7

Estrellas en GitHub: 123
Forks en GitHub: 24

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# OpenTiny NEXT-SDKs: Built-in WebMCP & Polyfill + WebSkills + WebAgent <p align="center"> <a href="https://opentiny.design" target="_blank" rel="noopener noreferrer"> <img alt="OpenTiny Logo" src="logo.svg" height="100" style="max-width:100%;"> </a> </p> English | [简体中文](README.zh-CN.md) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/opentiny/webmcp-sdk) <p align="center"> <strong>A front-end intelligent application development and browser automation toolkit. It turns existing apps intelligent via WebMCP + WebSkills, and provides webmcp-cli to perceive and control any webpage with zero refactoring, giving them out-of-the-box AI-Native capabilities.</strong> </p> <p align="center"> <a href="https://docs.opentiny.design/next-sdk/">📖 Docs</a> | <a href="#-quick-start">🚀 Quick Start</a> | <a href="#-webmcp--polyfill">🌐 WebMCP & Polyfill</a> | <a href="#-scenarios">💡 Scenarios</a> </p> > **Next-Gen AI Protocol**: OpenTiny NEXT-SDKs is built on the **WebMCP (Model Context Protocol for Web)**. It is fully compatible with the native `document.modelContext` API (currently in experimental stage in browsers like Chrome), allowing your web apps to be controlled by AI via a standardized protocol. > [!TIP] > **✨ Command-line Automation & AI Skills**: > We now offer **`webmcp-cli`** (browser control & polyfill auto-injection CLI) and **`webmcp-skill`** (standard instructions and sub-skills like Excalidraw drawing for AI agents). Together, they enable AI agents to perform complex, fine-grained tasks and "remote-drive" any webpage out of the box. --- **OpenTiny NEXT-SDKs** is a front-end intelligent application development and browser automation toolkit. Beyond enabling the "WebMCP + WebSkills" model to expose page operations as standardized tools in just a few lines of code, it features **`webmcp-cli`** (browser perception and control) and **`webmcp-skill`** (agent skills library). Combined with our **Polyfill**, not only can you build future-proof AI-Native apps in today's browsers, but you can also let AI agents automatically perceive and control any webpage with zero source code modifications. ## 📑 Table of Contents - [✨ Main Features](#-main-features) - [🌐 WebMCP & Polyfill](#-webmcp--polyfill) - [🚀 Quick Start](#-quick-start) - [📦 Core Packages](#-core-packages) - [💻 WebMCP CLI & Agent Skills](#-webmcp-cli--agent-skills) - [💡 Core Concepts](#-core-concepts) - [📖 Scenarios](#-scenarios) - [🛠️ Contributing](#️-contributing) - [📄 License](#-license) ## ✨ Main Features - 🔌 **Standard WebMCP Implementation**: Fully implements the browser version of the MCP protocol, making front-ends "AI-Callable" via a unified standard. - 📡 **Remote AI Control**: Connect seamlessly to **WebAgent services**, allowing AI to easily and stably call your front-end tools remotely. - 🛠️ **Built-in Polyfill Support**: Provides `document.modelContext` / `document.modelContext` patches for current browsers, ensuring today's code works seamlessly and transitions to native support in the future. - 🎯 **Zero-Refactor Intelligence**: Expose business logic and UI operations as tools without changing your app's core architecture. - 🧩 **WebSkills Abstraction**: Organizes tools into "Business Skills" for progressive disclosure. - 🤖 **AI Chat Components**: Provides out-of-the-box `@opentiny/next-remoter` for an instant AI remote controller. ## 🌐 WebMCP & Polyfill ### What is WebMCP? WebMCP is an extension of the Model Context Protocol specifically for web browsers. It defines how a web page provides "Tools" and "Resources" to AI agents. In the near future, browsers will provide a native `document.modelContext` object to manage these capabilities. ### Why Polyfill? Since native APIs are still experimental, **OpenTiny NEXT-SDKs provides a powerful Polyfill**. By calling `initializeBuiltinWebMCP()`, the SDK will: 1. **Injects `document.modelContext`**: Provides a standard-compliant API for tool registration. By default it **forces the JS polyfill** (`forcePolyfill: true`) over Chromium's experimental native implementation, which can crash the renderer on `getTools()`. Pass `{ forcePolyfill: false }` only when native WebMCP is confirmed stable. 2. **Automated Routing & Bridging**: Automatically handles message synchronization and tool invocation across different page paths and iframes. Call this at the page entry (or via `registerPageAgentTool()`) before registering tools or handing `document.modelContext` to an Agent. ### 📡 Cross-Page & Remote Control One of the core highlights of OpenTiny NEXT-SDKs is its support for "cross-environment controllability" of pages. With the help of the built-in WebMCP Polyfill and `@opentiny/next-remoter`, you can achieve: - **Automated Bridging**: The underlying layer automatically handles message synchronization and tool invocations across different page paths and iframes. - **Persistent Session ID**: Establish long-term connections with cloud AI orchestrators. - **Cross-time Collaboration**: Even if the user isn't actively interacting, AI can remotely trigger page tools based on instructions sent by the business system. - **High-level Business Automation**: Converts front-end DOM operations and business component APIs into execution units in automated flows, achieving app-level "remote driving". #### Connection Example Through `WebMcpClient`, we can remotely call and control the built-in WebMCP tools of the browser via a cloud-based web-agent: ```typescript import { WebMcpClient } from '@opentiny/next-sdk' const client = new WebMcpClient() // Connect to the WebAgent service const { sessionId } = await client.connect({ agent: true, builtin: true, // Enable built-in WebMCP proxy url: 'https://agent.opentiny.design/api/v1/webmcp-trial/mcp' }) console.log('Connected! Session ID:', sessionId) // Now your app can be controlled remotely via this sessionId ``` > [!TIP] > The URL above is a public test server provided by OpenTiny for testing purposes. For production use, you should deploy your own WebAgent instance. > Source code: [https://github.com/opentiny/web-agent](https://github.com/opentiny/web-agent) ## 🚀 Quick Start Turn your front-end application into an AI-capable one in just a few lines of code. ### Step 1: Install Dependencies ```bash npm install @opentiny/next-sdk ``` ### Step 2: Initialize WebMCP Polyfill (Recommended) Add this to your application's entry point (e.g., `main.ts` or `app.js`): ```typescript import { initializeBuiltinWebMCP } from '@opentiny/next-sdk' // Initialize Polyfill and Bridging Mechanism initializeBuiltinWebMCP() ``` Now, you can use the standard `document.modelContext` anywhere in your app to register tools: ```typescript // Register a tool that can be called by AI const abortController = new AbortController() document.modelContext.registerTool({ name: 'get_user_info', description: 'Get current user information', inputSchema: { type: 'object', properties: { userId: { type: 'string' } } }, execute: async (args) => { // Write your business logic here return { content: [{ type: 'text', text: `Info for user ${args.userId}...` }] } } }, { signal: abortController.signal }) // To unregister the tool when it's no longer needed, simply call abort() // abortController.abort() ``` ✅ **Done!** Your app is now an MCP Server. You can connect it to any MCP-compatible client or use our [TinyRemoter](#-cross-page--remote-control) to chat with the app directly. ## 📦 Core Packages ### @opentiny/next-sdk (Current Package) The core SDK package, providing: - **Built-in WebMCP Polyfill**: Injects `document.modelContext` and sets up the bridging mechanism for seamless AI-to-page communication. - **WebMcpServer**: Managed MCP server for full control over lifecycle and transport layers. - **WebMcpClient**: MCP client for connecting to WebAgent or other remote services. - **WebAgent**: High-level intelligent agent orchestration logic. - **Transport Layer**: Support for MessageChannel, SSE, HTTP, and Chrome Extension messaging. ### @opentiny/next-remoter Vue3 AI chat component based on TinyRobot, providing: - Integrated AI assistant UI. - MCP Plugin marketplace. - Dynamic WebSkills discovery and execution. ### @opentiny/webmcp-cli A CLI tool based on `puppeteer-core` used to control Chrome browsers and expose WebMCP interfaces: - **Browser Takeover**: Automatically starts or connects to a local Chrome with debugging ports via Chrome DevTools Protocol (CDP). - **Auto-Injection**: When browser tabs open, it detects and automatically injects the WebMCP polyfill and page manipulation tools (`page-agent-tool`). - **Unified Tool Protocol**: Maps page operations to standard MCP interfaces, allowing AI agents to call them directly. ### webmcp-skill Guidelines and domain-specific skills for third-party AI agents interacting with web pages: - **Prompt Optimization**: Built-in comprehensive system prompts and usage specifications to assist external LLM agents in accurately using the CLI to control pages. - **Domain-Specific Skills**: Provides sub-skills like Excalidraw canvas commands (`excalidraw_execute_command`) for high-difficulty granular web operations. --- ## 💻 WebMCP CLI & Agent Skills With the WebMCP CLI, you can treat the browser as an MCP server, directly exposing page manipulation interfaces to AI Agents. Running Puppeteer in the background to drive a real Chrome browser, it maps traditional page interactions (click, input, scroll, etc.) into standard MCP Tool calls. ### 🚀 Getting Started #### 1. Installation You can install it globally via NPM: ```bash npm install -g @opentiny/webmcp-cli ``` Or for local debugging within the current Monorepo: ```bash cd packages/webmcp-cli pnpm build npm install -g . ``` #### 2. Open a Webpage Navigate to a specific URL in Chrome and prepare the environment: ```bash webmcp-cli tabs open https://excalidraw.com ``` #### 3. Get Browser State View the current page state, including URL, title, open tabs, and **the list of automatically injected and native MCP tools**. It also returns an indexed DOM tree: ```bash webmcp-cli state ``` The output will include elements like `[18]<button>Search</button>` with their index and the corresponding MCP interface names. #### 4. Execute an MCP Tool Use JSON-formatted arguments to directly execute registered MCP tools on the page: ```bash # Click a button with DOM index 18 webmcp-cli run page-agent-tool '{"action": "click", "index": 18}' # Fill text into an input field with DOM index 13 webmcp-cli run page-agent-tool '{"action": "fill", "index": 13, "text": "Model Context Protocol"}' ``` ### 🧠 Agent Skill Guidelines In the `packages/webmcp-skill` directory, we have defined a set of standard **Agent Skills**. When LLMs (like Claude or Gemini) connect to a webpage as an agent, they read `SKILL.md` to learn how to properly issue CLI commands. For complex pages, we also pair them with domain-specific sub-skills: - **Excalidraw Canvas Tools (`domains/excalidraw.md`)**: Instructs the Agent to use `excalidraw_execute_command` to draw shapes and diagrams when the URL contains `excalidraw.com`. - **Baidu Search Tool**: Guides the Agent to automatically issue searches and pull page results. This gives NEXT-SDKs a complete ecosystem enabling external AI to autonomously "remote drive" any webpage. --- ## 💡 Core Concepts ### WebMCP Bridge Architecture Unlike traditional backend MCP, WebMCP focuses on the **Browser Context**. ```text ┌─────────────────────────────────────────────────────────────┐ │ Web Browser │ │ ┌──────────────────┐ ┌───────────────────┐ │ │ │ Front-end App │◄── Bridging ──►│ AI Assistant │ │ │ │ (WebMCP Server) │ Mechanism │ (MCP Client) │ │ │ └──────────────────┘ └───────────────────┘ │ │ ▲ │ │ └───────────┼──────────────────────────────────┼──────────────┘ │ (Standard Protocol) │ └──────────────────────────────────┘ ``` 1. **Register Tools**: Use `document.modelContext.registerTool` to declare your app's capabilities, with support for automatic unregistration via `AbortSignal`. 2. **Bridge Synchronization**: Our bridging mechanism automatically routes AI requests to the correct page or iframe, even if the user has switched pages. 3. **Direct Execution**: Tools run directly in the page environment, allowing access to the DOM, component state, and local APIs. ### Underlying Transport and Engine Layer Although you can simply use `document.modelContext.registerTool` for daily development, NEXT-SDKs retains the full core MCP protocol implementation internally for advanced scheduling: - **WebMcpServer / WebMcpClient**: Responsible for handling underlying JSON-RPC messages, Schema validation, and channel handshakes. It is recommended to only understand these when expanding infrastructure; business apps should avoid calling them directly. ## 📖 Scenarios - **🤝 Smart Customer Service**: Quickly build an AI customer service system that supports tool calls. - **📚 Doc Assistant**: Add intelligent Q&A functionality to documentation websites. - **🛠️ Dev Tools**: Build developer auxiliary tools that support code generation and analysis. - **🌐 Browser Extensions**: Develop browser plugins with AI capabilities. - **🏢 Enterprise Apps**: Add intelligent capabilities to enterprise applications. - **📊 Data Analysis**: Build intelligent data analysis and visualization applications. - **✍️ Content Creation**: Develop AI-assisted content creation tools. ## 🛠️ Contributing We welcome all forms of contribution! Whether it's reporting bugs, suggesting new features, improving documentation, or submitting code, we appreciate it. ### Prerequisites Before you start developing, please make sure your environment meets the following requirements: - **Node.js** >= 18.0.0 - **pnpm** >= 8.0.0 - **Git** Latest version ### Get the Code ```bash # Clone the repository git clone https://github.com/opentiny/next-sdk.git cd next-sdk # Install dependencies pnpm install ``` ### Project Structure ```text next-sdk/ ├── packages/ │ ├── next-sdk/ # Core SDK package │ │ ├── agent/ # WebAgent implementation │ │ ├── client/ # WebMCP client │ │ ├── server/ # WebMCP server │ │ ├── transport/ # Transport layer implementation │ │ ├── McpSdk.ts # MCP SDK encapsulation │ │ ├── index.ts # Main entry │ │ ├── package.json │ │ └── README.md │ ├── next-remoter/ # Vue3 AI Chat Component │ │ ├── src/ │ │ │ ├── components/ # Component implementation │ │ │ └── composable/ # Composables │ │ ├── package.json │ │ └── README.md │ ├── webmcp-cli/ # CLI tool for browser control via WebMCP │ │ ├── src/ # CLI main implementation │ │ ├── webmcp-tools/ # Injected page tools (e.g. Excalidraw, Baidu) │ │ ├── package.json │ │ └── README.md │ ├── webmcp-skill/ # Guidelines and domain-specific skills for AI agents │ │ ├── SKILL.md # Master instruction file for agents │ │ └── domains/ # Domain-specific instructions (e.g., Excalidraw) │ └── doc-ai/ # Doc AI example app ├── docs/ # Project docs ├── pnpm-workspace.yaml # pnpm workspace config ├── package.json └── README.md ``` ## 📚 Related Resources ### Official Docs - [OpenTiny NEXT-SDKs Official Docs](https://docs.opentiny.design/next-sdk/) - [TinyRobot Remoter Component Docs](https://docs.opentiny.design/next-sdk/guide/tiny-robot-remoter.html) - [API Reference](https://docs.opentiny.design/next-sdk/api/) ### Related Projects - [OpenTiny](https://github.com/opentiny) - OpenTiny Organization Homepage - [TinyVue](https://github.com/opentiny/tiny-vue) - Enterprise Vue Component Library - [TinyEngine](https://github.com/opentiny/tiny-engine) - Low-code Engine - [TinyRobot](https://github.com/opentiny/tiny-robot) - AI Chat Component ### WebMCP + WebSkills Best Practice Projects It is recommended to refer directly to the following example projects, clone or implement them according to your tech stack: | Tech Stack | Example Project | Description | | ----------- | ----------------------------------------- | --------------------------------------------------------------------------------------- | | **Vue** | [doc-ai](packages/doc-ai) | Vue3 + Vite, best practices for local WebMCP / Polyfill mode | | **Angular** | [doc-ai-angular](packages/doc-ai-angular) | Angular main app + iframe Remoter, connected to WebMCP via MessageChannel | | **React** | [doc-ai-react](packages/doc-ai-react) | React main app + iframe Remoter, similar WebMCP architecture to Vue version | Accompanying Documentation: - [Vue Best Practice with WebMCP](docs/guide/vue-webmcp-best-practice.md) - [Angular Best Practice with WebMCP](docs/guide/angular-webmcp-best-practice.md) --- ## 📄 License [MIT](https://github.com/opentiny/next-sdk/blob/main/LICENSE) Copyright (c) 2024-present OpenTiny Team ## 🙏 Acknowledgments Thanks to all contributors to the OpenTiny NEXT-SDKs project! [![contributors](https://contrib.rocks/image?repo=opentiny/next-sdk)](https://github.com/opentiny/next-sdk/graphs/contributors)

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