Build MCP servers, which expose tools and data to AI agents, with mcp-use. The material covers server functions, reusable prompts, and interactive React widgets, but this skill is deprecated and points to mcp-app-builder as its replacement.
DEPRECATED: This skill has been replaced by `mcp-app-builder`. Check if `mcp-app-builder` is available in the skills folder. If not, install it: `npx skills install mcp-use/mcp-use --skill mcp-app-builder` Use `mcp-app-builder` instead of this skill. Build Model Context Protocol (MCP) servers with mcp-use framework. Use when creating MCP servers, defining tools/resources/prompts, working with mcp-use, bootstrapping MCP projects, or when user mentions MCP development, tools, resources, or prompts.
Review the instructions the agent will receive before you install.
Build production-ready MCP servers with tools, resources, prompts, and interactive widgets using mcp-use.
Decompose user requests into tools, widgets, and resources. Decide what needs UI vs text.
Read design-and-architecture.md: when planning what to build, deciding tool vs widget, or designing UX flows.
server.tool(), server.resource(), server.prompt() coderesources/ folderimport {
MCPServer,
text,
object,
markdown,
html,
image,
widget,
error,
} from "mcp-use/server";
import { z } from "zod";
const server = new MCPServer({ name: "my-server", version: "1.0.0" });
// Tool
server.tool(
{
name: "my-tool",
description: "...",
schema: z.object({ param: z.string().describe("...") }),
},
async ({ param }) => text("result"),
);
// Resource
server.resource(
{ uri: "config://settings", name: "Settings", mimeType: "application/json" },
async () => object({ key: "value" }),
);
// Prompt
server.prompt(
{
name: "my-prompt",
description: "...",
schema: z.object({ topic: z.string() }),
},
async ({ topic }) => text(`Write about ${topic}`),
);
server.listen();
Response helpers: text(), object(), markdown(), html(), image(), audio(), binary(), error(), mix(), widget()
Server methods: server.tool(), server.resource(), server.resourceTemplate(), server.prompt(), server.listen()
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Set up an agent that replies in Slack or Microsoft Teams using CopilotKit's guided CLI workflow. It covers project preparation, agent creation, channel configuration, a persistent host process, and verification with a real message.
Guides development of ChatGPT apps with interactive widgets using mcp-use and OpenAI Apps SDK, covering server tools, React interfaces, and shared state. This skill is deprecated and directs users to mcp-app-builder.
Helps integrate CopilotKit into an app by consulting current documentation and source code. Covers chat interfaces, agent connections, shared state, and troubleshooting, with guidance on checking configuration and avoiding incompatible API versions.
Implement and customize managed CopilotKit Channels so agents can reply in Slack or Microsoft Teams. It covers channel handlers, persistent runtime connections, Teams setup, and checks for silent failures such as missing permissions or incompatible package versions.
Use the CopilotKit CLI to check app connections, credentials, and agent responses before investigating code. It also guides project creation, integration into existing apps, hosted project selection, typed agent identifier generation, and thread history imports.
Keeps CopilotKit documentation aligned with released Inspector panels, the views shown in its local web overlay. It updates reader guidance and panel mappings when panels change, and checks quickstart instructions against supported platforms.