WebMCP

Draft Community Group Report ,

More details about this document
This version:
https://webmachinelearning.github.io/webmcp
Issue Tracking:
GitHub
Editors:
( Microsoft )
( Google )
( Google )
Not Ready For Implementation

This spec is not yet ready for implementation. It exists in this repository to record the ideas and promote discussion.

Before attempting to implement this spec, please contact the editors.

Copyright © 2026 the Contributors to the WebMCP Specification, published by the Web Machine Learning Community Group under the W3C Community Contributor License Agreement (CLA) . A human-readable summary is available.

Abstract

The WebMCP API enables web applications to provide JavaScript-based tools to AI agents.

Status of this document

This specification was published by the Web Machine Learning Community Group . It is not a W3C Standard nor is it on the W3C Standards Track. Please note that under the W3C Community Contributor License Agreement (CLA) there is a limited opt-out and other conditions apply. Learn more about W3C Community and Business Groups .

1. Introduction

WebMCP API is a new JavaScript interface that allows web developers to expose their web application functionality as “tools” - JavaScript functions with natural language descriptions and structured schemas that can be invoked by agents , browser’s agents , and assistive technologies . Web pages that use WebMCP can be thought of as Model Context Protocol [MCP] servers that implement tools in client-side script instead of on the backend. WebMCP enables collaborative workflows where users and agents work together within the same web interface, leveraging existing application logic while maintaining shared context and user control.

2. Terminology

An agent is an autonomous assistant that can understand a user’s goals and take actions on the user’s behalf to achieve them. Today, these are typically implemented by large language model (LLM) based AI platforms , interacting with users via text-based chat interfaces.

A browser’s agent is an agent provided by or through the browser that could be built directly into the browser or hosted by it, for example, via an extension or plug-in.

An AI platform is a provider of agentic assistants such as OpenAI’s ChatGPT, Anthropic’s Claude, or Google’s Gemini.

3. Security and privacy considerations

4. Accessibility considerations

5. API 

partial interface Navigator {
  [SecureContext, SameObject] readonly attribute ModelContextContainer modelContext;
};
[Exposed=Window, SecureContext]
interface ModelContextContainer {
};
6. Acknowledgements Thanks to Brandon Walderman, Leo Lee, Andrew Nolan, David Bokan, Khushal Sagar, Hannah Van Opstal, Sushanth Rajasankar for the initial explainer, proposals and discussions that established the foundation for this specification. Also many thanks to Alex Nahas and Jason McGhee for sharing early implementation experience. Finally, thanks to the participants of the Web Machine Learning Community Group for feedback and suggestions.

Index

Terms defined by this specification

Terms defined by reference

References

Normative References

[HTML]
Anne van Kesteren; et al. HTML Standard . Living Standard. URL: https://html.spec.whatwg.org/multipage/
[MCP]
Model Context Protocol (MCP) Specification . URL: https://modelcontextprotocol.io/specification/latest
[WAI-ARIA-1.2]
Joanmarie Diggs; et al. Accessible Rich Internet Applications (WAI-ARIA) 1.2 . URL: https://w3c.github.io/aria/
[WEBIDL]
Edgar Chen; Timothy Gu. Web IDL Standard . Living Standard. URL: https://webidl.spec.whatwg.org/

IDL Index 

partial interface Navigator {
  [SecureContext, SameObject] readonly attribute ModelContextContainer modelContext;
};
[Exposed=Window, SecureContext]
interface ModelContextContainer {
};