mcp-use - The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude and MCP Servers for AI Agents.

The fullstack MCP framework

Build MCP Apps for ChatGPT / Claude and MCP Servers for AI Agents - in TypeScript and Python.

Build
with the mcp-use SDK

Preview
with the MCP Inspector

Deploy
to production in one command

Quickstart

TypeScript
Python

npx create-mcp-use-app@latest

Or create a server manually:

import { MCPServer, text } from "mcp-use/server";
import { z } from "zod";

const server = new MCPServer({
  name: "my-server",
  version: "1.0.0",
});

server.tool({
  name: "get_weather",
  description: "Get weather for a city",
  schema: z.object({ city: z.string() }),
}, async ({ city }) => {
  return text(`Temperature: 72°F, Condition: sunny, City: ${city}`);
});

await server.listen(3000);
// Inspector at http://localhost:3000/inspector

Full TypeScript Server Documentation

pip install mcp-use

from typing import Annotated
from mcp.types import ToolAnnotations
from pydantic import Field
from mcp_use import MCPServer

server = MCPServer(name="Weather Server", version="1.0.0")

@server.tool(
    name="get_weather",
    description="Get current weather information for a location",
    annotations=ToolAnnotations(readOnlyHint=True, openWorldHint=True),
)
async def get_weather(
    city: Annotated[str, Field(description="City name")],
) -> str:
    return f"Temperature: 72°F, Condition: sunny, City: {city}"

server.run(transport="streamable-http", port=8000)
# Inspector at http://localhost:8000/inspector

Full Python Server Documentation

MCP Apps

MCP Apps let you build interactive widgets that work across Claude, ChatGPT, and other MCP clients - write once, run everywhere.

import { MCPServer, widget } from "mcp-use/server";
import { z } from "zod";

const server = new MCPServer({ name: "weather-app", version: "1.0.0" });

server.tool({
  name: "get-weather",
  description: "Get weather for a city",
  schema: z.object({ city: z.string() }),
  widget: "weather-display", // references resources/weather-display/widget.tsx
}, async ({ city }) => {
  return widget({
    props: { city, temperature: 22, conditions: "Sunny" },
    message: `Weather in ${city}: Sunny, 22°C`,
  });
});

await server.listen(3000);

Widgets in resources/ are auto-discovered - no manual registration needed.

MCP Apps Guide

Build widgets with React, auto-discovery, and client-side hooks.

Apps SDK compatibility

Understand how MCP Apps run in ChatGPT.

Templates

Ready-to-use MCP Apps and Servers you can deploy in one click or remix as your own.

Chart Builder

Natural-language chart generation.

Diagram Builder

Conversational diagramming.

Widget Gallery

Reference patterns for every widget type.

Browse all templates

Full gallery with demo URLs and one-click deploy buttons.

Inspector

Test and debug your MCP servers interactively. The Inspector is auto-included in every server:

server.listen(3000);
// Inspector at http://localhost:3000/inspector

Or use the hosted inspector at inspector.mcp-use.com, or standalone:

npx @mcp-use/inspector --url http://localhost:3000/mcp

Inspector Documentation

Deploy

Ship to production in one command:

npx @mcp-use/cli login
npx @mcp-use/cli deploy

Or connect a GitHub repo on manufact.com - production-ready with observability, metrics, logs, and branch deployments.

Also: MCP Agent & MCP Client

mcp-use is fullstack. Alongside MCP Servers and MCP Apps, it ships a full MCP Agent and MCP Client implementation.

MCP Agent - Build AI agents that use MCP servers

Connect any LLM (OpenAI, Anthropic, Google, LangChain) to any MCP server.

from langchain_openai import ChatOpenAI
from mcp_use import MCPAgent, MCPClient

client = MCPClient.from_dict({ "mcpServers": { "fs": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"] } } })
agent = MCPAgent(llm=ChatOpenAI(model="gpt-5.5"), client=client)
result = await agent.run("List all files in the directory")

https://mintcdn.com/mcpuse/C8kWie3B44RcXcXB/images/pythonlogo.svg?fit=max&auto=format&n=C8kWie3B44RcXcXB&q=85&s=c7e14bf0a4c75ce1e6cd1187fe39913b

Python Agent

https://mintcdn.com/mcpuse/C8kWie3B44RcXcXB/images/typescriptlogo.svg?fit=max&auto=format&n=C8kWie3B44RcXcXB&q=85&s=42b7b5880c4065c7532afa4a000d6fc0

TypeScript Agent

MCP Client - Connect to any MCP server programmatically

Fully spec-compliant: tools, resources, prompts, sampling, elicitation, logging, notifications.

import { MCPClient } from "mcp-use";
const client = new MCPClient({ mcpServers: { calculator: { command: "npx", args: ["-y", "@modelcontextprotocol/server-everything"] } } });
await client.createAllSessions();
const result = await client.getSession("calculator").callTool("add", { a: 5, b: 3 });