An MCP app is a standard MCP server that also serves UI resources — interactive components rendered inline in the chat surface. Build once, runs in Claude and ChatGPT and any other host that implements the apps surface.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbuild-mcp-appExecute the skills CLI command in your project's root directory to begin installation:
Fetches build-mcp-app from anthropics/claude-plugins-official and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate build-mcp-app. Access via /build-mcp-app in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
16.2K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
16.2K
stars
An MCP app is a standard MCP server that also serves UI resources — interactive components rendered inline in the chat surface. Build once, runs in Claude and ChatGPT and any other host that implements the apps surface.
The UI layer is additive. Under the hood it's still tools, resources, and the same wire protocol. If you haven't built a plain MCP server before, the build-mcp-server skill covers the base layer. This skill adds widgets on top.
Don't add UI for its own sake — most tools are fine returning text or JSON. Add a widget when one of these is true:
| Signal | Widget type |
|---|---|
| Tool needs structured input Claude can't reliably infer | Form |
| User must pick from a list Claude can't rank (files, contacts, records) | Picker / table |
| Destructive or billable action needs explicit confirmation | Confirm dialog |
| Output is spatial or visual (charts, maps, diffs, previews) | Display widget |
| Long-running job the user wants to watch | Progress / live status |
If none apply, skip the widget. Text is faster to build and faster for the user.
Before building a widget, check if elicitation covers it. Elicitation is spec-native, zero UI code, works in any compliant host.
| Need | Elicitation | Widget |
|---|---|---|
| Confirm yes/no | ✅ | overkill |
| Pick from short enum | ✅ | overkill |
| Fill a flat form (name, email, date) | ✅ | overkill |
| Pick from a large/searchable list | ❌ (no scroll/search) | ✅ |
| Visual preview before choosing | ❌ | ✅ |
| Chart / map / diff view | ❌ | ✅ |
| Live-updating progress | ❌ | ✅ |
If elicitation covers it, use it. See ../build-mcp-server/references/elicitation.md.
Hosted streamable-HTTP server. Widget templates are served as resources; tool results reference them. The host fetches the resource, renders it in an iframe sandbox, and brokers messages between the widget and Claude.
┌──────────┐ tools/call ┌────────────┐
│ Claude │─────────────> │ MCP server │
│ host │<── result ────│ (remote) │
│ │ + widget ref │ │
│ │ │ │
│ │ resources/read│ │
│ │─────────────> │ widget │
│ ┌──────┐ │<── template ──│ HTML/JS │
│ │iframe│ │ └────────────┘
│ │widget│ │
│ └──────┘ │
└──────────┘
Same widget mechanism, but the server runs locally inside an MCPB bundle. Use this when the widget needs to drive a local application — e.g., a file picker that browses the actual local disk, a dialog that controls a desktop app.
For MCPB packaging mechanics, defer to the build-mcpb skill. Everything below applies to both shapes.
A widget-enabled tool has two separate registrations:
_meta.ui.resourceUri. Its handler returns plain text/JSON — NOT the HTML.When Claude calls the tool, the host sees _meta.ui.resourceUri, fetches that resource, renders it in an iframe, and pipes the tool's return value into the iframe via the ontoolresult event.
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { registerAppTool, registerAppResource, RESOURCE_MIME_TYPE }
from "@modelcontextprotocol/ext-apps/server";
import { z } from "zod";
const server = new McpServer({ name: "contacts", version: "1.0.0" });
// 1. The tool — returns DATA, declares which UI to show
registerAppTool(server, "pick_contact", {
description: "Open an interactive contact picker",
inputSchema: { filter: z.string().optional() },
_meta: { ui: { resourceUri: "ui://widgets/contact-picker.html" } },
}, async ({ filter }) => {
const contacts = await db.contacts.search(filter);
// Plain JSON — the widget receives this via ontoolresult
return { content: [{ type: "text", text: JSON.stringify(contacts) }] };
});
// 2. The resource — serves the HTML
registerAppResource(
server,
"Contact Picker",
"ui://widgets/contact-picker.html",
{},
async () => ({
contents: [{
uri: "ui://widgets/contact-picker.html",
mimeType: RESOURCE_MIME_TYPE,
text: pickerHtml, // your HTML string
}],
}),
);
The URI scheme ui:// is convention. The mime type MUST be RESOURCE_MIME_TYPE ("text/html;profile=mcp-app") — this is how the host knows to render it as an interactive iframe, not just display the source.
App classInside the iframe, your script talks to the host via the App class from @modelcontextprotocol/ext-apps. This is a persistent bidirectional connection — the widget stays alive as long as the conversation is active, receiving new tool results and sending user actions.
<script type="module">
/* ext-apps bundle inlined at build time → globalThis.ExtApps */
/*__EXT_APPS_BUNDLE__*/
const { App } = globalThis.ExtApps;
const app = new App({ name: "ContactPicker", version: "1.0.0" }, {});
// Set handlers BEFORE connecting
app.ontoolresult = ({ content }) => {
const contacts = JSON.parse(content[0].text);
render(contacts);
};
await app.connect();
// Later, when the user clicks something:
function onPick(contact) {
app.sendMessage({
role: "user",
content: [{ type: "text", text: `Selected contact: ${contact.id}` }],
});
}
</script>
The /*__EXT_APPS_BUNDLE__*/ placeholder gets replaced by the server at startup with the contents of @modelcontextprotocol/ext-apps/app-with-deps — see references/iframe-sandbox.md for why this is necessary and the rewrite snippet. Do not import { App } from "https://esm.sh/..."; the iframe's CSP blocks the transitive dependency fetches and the widget renders blank.
| Method | Direction | Use for |
|---|---|---|
app.ontoolresult = fn |
Host → widget | Receive the tool's return value |
app.ontoolinput = fn |
Host → widget | Receive the tool's input args (what Claude passed) |
app.sendMessage({...}) |
Widget → host | Inject a message into the conversation |
app.updateModelContext({...}) |
Widget → host | Update context silently (no visible message) |
app.callServerTool({name, arguments}) |
Widget → server | Call another tool on your server |
app.openLink({url}) |
Widget → host | Open a URL in a new tab (sandbox blocks window.open) |
app.getHostContext() / app.onhostcontextchanged |
Host → widget | Theme (light/dark), locale, etc. |
sendMessage is the typical "user picked something, tell Claude" path. updateModelContext is for state that Claude should know about but shouldn't clutter the chat. openLink is required for any outbound navigation — window.open and <a target="_blank"> are blocked by the sandbox attribute.
What widgets cannot do:
callServerTool)app.openLink({url})data: URLs server-sideKeep widgets small and single-purpose. A picker picks. A chart displays. Don't build a whole sub-app inside the iframe — split it into multiple tools with focused widgets.
Install:
npm install @modelcontextprotocol/sdk @modelcontextprotocol/ext-apps zod express
Server (src/server.ts):
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Related Skills
mobile-app-ui-design
56ceorkm/mobile-app-ui-design
Frontendtag: appfrontend-design
662anthropics/claude-code
Frontendsame categoryui-animation
242mblode/agent-skills
Frontendsame categorypremium-frontend-ui
236github/awesome-copilot
Frontendsame categoryantigravity-design-expert
209sickn33/antigravity-awesome-skills
Frontendsame categoryhigh-end-visual-design
193leonxlnx/taste-skill
Frontendsame categoryReviews
4.6★★★★★49 reviews- HHana Martin★★★★★Dec 28, 2024
We added build-mcp-app from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- DDhruvi Jain★★★★★Dec 24, 2024
build-mcp-app has been reliable in day-to-day use. Documentation quality is above average for community skills.
- MMia Chawla★★★★★Dec 16, 2024
Useful defaults in build-mcp-app — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- TTariq Anderson★★★★★Dec 12, 2024
Solid pick for teams standardizing on skills: build-mcp-app is focused, and the summary matches what you get after install.
- AAnaya Malhotra★★★★★Nov 23, 2024
build-mcp-app is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- HHana Taylor★★★★★Nov 23, 2024
build-mcp-app fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- CCharlotte Khanna★★★★★Nov 19, 2024
Useful defaults in build-mcp-app — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- OOshnikdeep★★★★★Nov 15, 2024
Solid pick for teams standardizing on skills: build-mcp-app is focused, and the summary matches what you get after install.
- TTariq Kim★★★★★Nov 7, 2024
We added build-mcp-app from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- TTariq Huang★★★★★Nov 3, 2024
build-mcp-app has been reliable in day-to-day use. Documentation quality is above average for community skills.
showing 1-10 of 49
1 / 5Discussion
Comments — not star reviews- No comments yet — start the thread.