ext-apps: Standard for UIs Embedded in AI Chatbots with MCP Protocol

Introduction

The ext-apps repository hosts the official specification and SDK for the Model Context Protocol (MCP) Apps. This protocol establishes a standard for embedding interactive user interfaces (UIs) directly within AI chatbot clients, served by MCP servers. It allows developers to build rich, dynamic UIs, such as charts, forms, and dashboards, that render seamlessly within conversational AI experiences like Claude and ChatGPT.

MCP Apps extend the core Model Context Protocol, enabling tools to declare UI resources. This means your AI tools can go beyond returning text or structured data, offering a fully interactive experience to users directly within their chat client.

Installation

Getting started with MCP Apps is straightforward. You can install the SDK via npm:

npm install -S @modelcontextprotocol/ext-apps

For a comprehensive guide, refer to the Quickstart Guide.

The repository also ships with four Agent Skills to accelerate development: create-mcp-app, migrate-oai-app, add-app-to-server, and convert-web-app. These skills can be installed in clients like Claude Code:

/plugin marketplace add modelcontextprotocol/ext-apps
/plugin install mcp-apps@modelcontextprotocol-ext-apps

Examples

The examples/ directory showcases various real-world use cases and starter templates for MCP Apps. Some notable examples include:

• Map: An interactive 3D globe viewer using CesiumJS.
• Three.js: An interactive 3D scene renderer.
• Sheet Music: Converts ABC notation to sheet music.
• PDF Server: An interactive PDF viewer with chunked loading.
• Starter Templates: Basic apps built with popular frameworks like React, Vue, Svelte, Preact, Solid, and Vanilla JS.

You can run all examples locally using the basic-host reference implementation:

git clone https://github.com/modelcontextprotocol/ext-apps.git
cd ext-apps
npm install
npm start

Then open http://localhost:8080/ in your browser.

Why Use MCP Apps?

While traditional MCP tools are excellent for returning text and structured data, they fall short when interactive UIs are required. MCP Apps fill this gap by providing a standardized method to deliver interactive UIs from MCP servers. These UIs render inline within the conversation, maintaining context across any compliant host.

The process involves:

1. Tool definition: Your tool declares a ui:// resource containing its HTML interface.
2. Tool call: The Large Language Model (LLM) calls the tool on your server.
3. Host renders: The host fetches the resource and displays it in a sandboxed iframe.
4. Bidirectional communication: The host passes tool data to the UI via notifications, and the UI can call other tools through the host.

This approach allows for powerful integrations, transforming AI chatbots into platforms for rich, interactive applications.

Links

• GitHub Repository: https://github.com/modelcontextprotocol/ext-apps
• Quickstart Guide: https://apps.extensions.modelcontextprotocol.io/api/documents/Quickstart.html
• API Documentation: https://apps.extensions.modelcontextprotocol.io/api/
• Specification (2026-01-26): https://github.com/modelcontextprotocol/ext-apps/blob/main/specification/2026-01-26/apps.mdx