WebMCP
WebMCP is a proposed web standard that enables websites to expose structured tools directly to in-browser AI agents through JavaScript functions, allowing for more efficient and reliable AI interactions with web applications.
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Product Information
Updated:Feb 28, 2026
What is WebMCP
WebMCP (Web Model Context Protocol) is an open-source JavaScript library and web standard being incubated by the W3C Web Machine Learning Community Group, developed jointly by engineers from Google and Microsoft. It serves as a bridge between websites and AI agents by providing a standardized way for web developers to define and expose their site's functionality as 'tools' that can be directly accessed by AI agents, browser assistants, and assistive technologies, without requiring backend server implementation.
Key Features of WebMCP
WebMCP (Web Model Context Protocol) is a proposed W3C web standard that enables websites to expose structured tools directly to in-browser AI agents through the navigator.modelContext API. It allows developers to define website functionalities as JavaScript functions with natural language descriptions and structured schemas, eliminating the need for screen scraping and improving the efficiency and reliability of AI-web interactions.
Structured Tool Registration: Allows developers to register website functionalities as tools with clear descriptions and JSON schemas that AI agents can directly call
Browser-Native Integration: Runs entirely in the browser tab, sharing the user's session and security context without requiring separate backend infrastructure
Declarative & Imperative APIs: Provides both HTML-based declarative and JavaScript-based imperative approaches for implementing AI-accessible tools
Built-in Development Tools: Includes DevTools integration and a Model Context Tool Inspector for debugging and testing tool implementations
Use Cases of WebMCP
E-commerce Integration: Enable AI agents to directly interact with shopping carts, product searches, and checkout processes through structured tools
Content Management: Allow AI agents to efficiently access and manage blog posts, articles, and other content through direct API calls instead of parsing HTML
Form Automation: Streamline form filling and data submission processes by providing AI agents with structured access to form fields and validation rules
Search Enhancement: Improve search functionality by allowing AI agents to directly query and filter content using structured parameters
Pros
Reduces computational overhead by ~67% compared to traditional screen scraping methods
Improves task accuracy to around 98% through structured interactions
Requires no backend infrastructure changes, working entirely in the browser
Provides standardized way for websites to interact with AI agents
Cons
Currently limited to Chrome browser with experimental features enabled
Faces adoption challenges due to chicken-and-egg problem between websites and agents
Still in early stages of development with potential API changes
Requires additional development effort to implement and maintain tool definitions
How to Use WebMCP
Enable WebMCP in Chrome: Go to chrome://flags, search for 'WebMCP for testing', enable it, and relaunch Chrome. This is required as WebMCP is currently in development trial.
Include WebMCP Script: Add the WebMCP script to your webpage by including <script src='webmcp.js'></script> in your HTML
Initialize WebMCP: Create a new WebMCP instance with custom options like: const mcp = new WebMCP({ color: '#4CAF50', position: 'top-right', size: '40px', padding: '15px' });
Register Tools: Register tools that AI agents can use by calling mcp.registerTool() with name, description, input schema, and execution function. Tools should be registered immediately after loading the script.
Register Prompts: Set up predefined templates for LLM interactions using mcp.registerPrompt() with name, description, parameters, and template function
Register Resources: Expose data and content for LLM context using mcp.registerResource() with name, description, URI configuration, and content retrieval function
Connect MCP Client: Start your MCP client (like Claude) and connect it to your webpage by clicking the blue widget in the corner and pasting the WebMCP token
Test Integration: Verify the setup by having your AI agent interact with the registered tools, prompts and resources on your webpage
WebMCP FAQs
WebMCP is an open source JavaScript library and web standard that allows websites to integrate with the Model Context Protocol. It enables web applications to expose their functionality as 'tools' - JavaScript functions with natural language descriptions and structured schemas that can be invoked by AI agents and assistive technologies.
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