The short definition
An MCP app is a product experience that lets an AI assistant reach outside the chat window. It usually combines a name, description, tools, permissions, and sometimes an embedded UI. The technical layer underneath is an MCP server.
The server exposes capabilities through the Model Context Protocol, while a host such as ChatGPT, Claude, Claude Code, or another MCP-compatible client decides how those capabilities appear to the user.
On this directory, we use app for the listing people browse, and server for the backend endpoint that exposes tools.
The three parts
Most MCP apps have three practical layers. Keeping them separate makes the whole ecosystem easier to understand.
- The app listing: name, icon, tagline, categories, examples, links, and platform surfaces.
- The MCP server: tools, auth, transport, schemas, and the code that reads or writes external systems.
- The host surface: ChatGPT apps, Claude connectors, Claude Code, IDEs, or other clients that connect to the server.
Why MCP matters
Before MCP, every AI app often needed a custom integration path. MCP gives builders a common way to expose tools, data, and workflows to multiple AI hosts.
That means a calendar, database, design tool, CRM, codebase, or analytics product can be made available to assistants in a predictable way instead of rebuilding the same connector again and again.
ChatGPT apps vs Claude connectors
A ChatGPT app is a ChatGPT-facing experience built on an MCP server, and it can optionally include an embedded UI. A Claude connector is a Claude-facing connection to an MCP server or service that gives Claude access to external context and tools.
Many products can support both. The useful question is not which label is better, but which host your users already work in and which actions your server can safely perform.