WebMCP

WebMCP (Web Model Context Protocol) is a browser-native implementation of the Model Context Protocol (MCP) that allows websites to expose structured tools and data directly to AI agents through the navigator.modelContext JavaScript API.¹⁾ First published in August 2025, WebMCP enables web applications to function as client-side MCP servers, eliminating the need for separate backend infrastructure to expose application capabilities to AI agents.²⁾

The Model Context Protocol, introduced by Anthropic in November 2024, established a standard for AI agents to communicate with external tools and data sources via server-side JSON-RPC connections.³⁾ While MCP proved effective for backend services, databases, and headless APIs, it left a gap for browser-based applications where business logic, user state, and authenticated context already resided in the client.⁴⁾

WebMCP addresses this gap by bringing MCP principles into the browser environment through a W3C Community Group standard developed jointly by Google and Microsoft.⁵⁾

WebMCP defines two primary types of data that websites expose to agents:

• Context — all data agents need to understand user activity, including content not currently visible on screen
• Tools — actions agents can perform on behalf of users, from answering questions to completing forms and executing transactions

Unlike server-side MCP, which uses persistent server connections over HTTP or stdio, WebMCP operates entirely client-side. Web developers register structured tools via the navigator.modelContext API, and browser-based AI agents can discover and invoke these tools directly without intermediate infrastructure.⁶⁾

The Chrome team uses the analogy of a customer service call center versus an in-store expert:⁷⁾

• MCP is available on any platform at any time, pulling up data and handling core tasks as needed
• WebMCP is available only on a specific website, helping agents understand the UI and interact with application-specific capabilities

Both share the same philosophy of structured tool discovery and predictable execution, but they address different deployment contexts. They are complementary, not competing, standards.

• Structured tool discovery — agents can programmatically ask “what can you do?” and receive a machine-readable list of available tools, parameters, and descriptions
• Predictable execution — explicit function calls replace guesswork, producing predictable outcomes
• No server required — the website itself becomes the tool surface, reusing existing application logic
• Shared context — agents and users work within the same web interface, maintaining shared state and user control
• Human-in-the-loop — designed for collaborative workflows where users retain oversight of agent actions

The WebMCP specification was authored by researchers from Microsoft (Brandon Walderman, Leo Lee, Andrew Nolan) and Google (David Bokan, Khushal Sagar, Hannah Van Opstal).⁸⁾ The repository has attracted over 2,100 stars on GitHub and 20 contributors as of early 2026.

In February 2026, Google announced that WebMCP was available for its Early Preview Program (EPP), allowing developers to experiment with the API in Chrome.⁹⁾

• Model Context Protocol (MCP)
• AI Agents