MCP and AI app glossary: plain-English definitions for owners

Getting your product into ChatGPT and Claude comes with a lot of new words. This glossary explains the ones owners actually meet, in plain English, with a link to the official source for each.

It reflects the sources as of 17 October 2026. The current MCP specification is version 2026-07-28, a big revision (what changed), and AI apps and SDKs adopt new versions at their own pace. OpenAI and Anthropic also rename things often, so check the linked pages before you build on a detail.

The basics

• Model Context Protocol (MCP). An open standard for connecting AI apps to outside tools and data. Anthropic created it and in December 2025 gave it to the Agentic AI Foundation, part of the Linux Foundation. It's run by maintainers in the open (governance). Both ChatGPT and Claude use it.
• MCP server. The piece you build or host. It offers tools (and optionally resources and prompts) to AI apps and calls your API when one is used (architecture). To an owner, "MCP server", "MCP app", "connector" and "plugin" often mean roughly the same thing seen from different sides. See turn your API into an MCP server.
• MCP host and MCP client. The host is the AI app a person uses, such as ChatGPT or Claude. Inside it, a client holds the connection to one server. The host decides what the AI may do and asks the person for consent (architecture).
• Remote MCP server. A server on the internet, reached over HTTPS, as opposed to a local one running on someone's own computer. ChatGPT's and Claude's directories only take remote servers (Claude's docs, OpenAI's docs). See MCP server hosting.

What a server offers

• Tool. An action the AI can choose to call, like search_events or get_order_status. Each has a name, a description and the inputs it takes. The spec says a person should be able to refuse a call (tools).
• Resource. Data the server shares as context, such as a file or a record, each with its own address (a URI). The AI app decides how to use it (resources).
• Prompt. A ready-made message template that a person picks on purpose, often from a slash menu (prompts).
• Structured content and output schema. A tool can return machine-readable JSON (structuredContent) alongside text. If the tool declares an outputSchema, its results must match it, which helps AI apps and interfaces rely on the shape (tools).
• Tool annotations. Labels on each tool that tell the AI app what it does: title, readOnlyHint (only reads), destructiveHint (may delete or overwrite), idempotentHint (safe to repeat) and openWorldHint (reaches outside systems). They're hints, and the spec tells clients not to trust them from servers they don't trust (schema). The directories care a lot: Claude's requires a title and a read-only or destructive hint on every tool (review criteria), and OpenAI asks for explicit read-only, destructive and open-world values (guidelines).

How AI apps connect

• Transport. How messages travel between AI app and server (transports). stdio runs the server as a local program on the same computer. Streamable HTTP sends each message as an HTTP request to one address, and is what remote servers use. The older HTTP with SSE transport has been deprecated since the 2025-03-26 spec; new servers should use Streamable HTTP.
• Elicitation. A way for a server to ask the person for more information mid-task, through the AI app. Form mode collects simple fields and must never ask for secrets. URL mode sends the person to a web page for things like signing in or paying (elicitation).
• Sampling. A way for a server to ask the AI app's own model to write something. Deprecated in 2026-07-28: servers should call an AI provider directly instead (sampling).
• Roots. A way for an AI app to tell a server which folders matter. Mostly for local coding tools, and also deprecated in 2026-07-28 (roots).
• Tasks. An optional, official extension for long-running work: the server hands back a task id and the AI app checks on progress later (tasks).

Sign-in (OAuth)

• OAuth 2.1 for MCP. The standard way a person lets ChatGPT or Claude act on their account with you, without handing over a password. Sign-in is optional in MCP, but servers that use it should follow the MCP authorization spec, which builds on OAuth 2.1 (authorization). Your MCP server checks tokens; a separate service usually issues them.
• Authorization server. The service that signs people in and issues tokens, often your existing identity provider. It publishes discovery metadata so AI apps can find its sign-in and token addresses (discovery).
• Protected resource metadata. A small public JSON file on your MCP server that says which authorization server to use. When an AI app calls without a token, the server answers 401 with a pointer to this file, and the sign-in flow starts from there (discovery).
• Client registration: CIMD and DCR. Before signing someone in, the AI app has to introduce itself to your authorization server. In the current spec the preferred way is a Client ID Metadata Document (CIMD): the AI app's client id is an HTTPS address describing it. Dynamic Client Registration (DCR), where the app registers itself on the fly, is now deprecated but kept for older servers (client registration). ChatGPT's portal accepts a registered client, DCR or CIMD (OpenAI auth), and Claude supports DCR and CIMD (Claude auth).
• PKCE. An extra check during sign-in that stops a stolen sign-in code from being used. MCP clients must use it (security considerations).
• Resource indicator (token audience). The AI app names your MCP server when it asks for a token, and your server must only accept tokens issued for it. That stops a token meant for one service being replayed against another (authorization).

ChatGPT and Claude terms

• Plugin (ChatGPT). What OpenAI's docs now call the package you publish for ChatGPT and Codex. It can hold an MCP connection, skills, or both (plugins). Older guides call this a ChatGPT app built with the Apps SDK; the old apps-sdk links now lead to the plugin docs.
• Plugin directory (ChatGPT). Where people find plugins in ChatGPT and Codex, formerly called the app directory. You submit from the Plugins page of the OpenAI platform after organization and domain verification (submission). See our ChatGPT guide.
• Connector (Claude). How Claude users see an MCP server. A directory connector has been through Anthropic's review; a custom connector is one a person or organization adds by pasting its address, with no review (directory vs custom, custom connectors).
• Connectors Directory (Claude). Anthropic's catalogue of reviewed connectors, used across Claude's apps. Listings are labelled Community or Verified, and you submit from any paid Claude plan (directory, submission). See our Claude guide.
• MCP Apps and widgets. Interactive interfaces, such as a seat map or a booking form, that a tool shows inside the chat. MCP Apps is an official MCP extension: the interface is an HTML resource that runs in a sandbox inside the AI app (MCP Apps). OpenAI's docs build ChatGPT interfaces on it (ChatGPT UI) and Claude supports it (Claude's MCP Apps docs). They're optional: an app can be tools only.
• Developer mode (ChatGPT). The setting that used to be needed to add your own MCP server to ChatGPT for testing. OpenAI's help centre now says you no longer need to turn it on: you add a custom server from Plugins and accept a risk warning, and full access, including write actions, is listed for Business and Enterprise/Edu workspaces on the web (custom MCP servers in ChatGPT).

Registries and testing

• MCP Registry. The official open catalogue of MCP servers, run by the MCP project. It stores details about servers, not their code, and is still in preview. You publish with the mcp-publisher tool under a namespace you prove you own, such as your domain (about, quickstart). Being listed there doesn't put you in ChatGPT's or Claude's directories. See where to list your MCP server.
• MCP SDKs. Official libraries for building servers and clients, in TypeScript, Python, C#, Go, Rust, Ruby, Java and more (SDKs).
• MCP Inspector. The official tool for trying a server by hand: list its tools, call them and see the raw responses (Inspector).

Common questions

### What is the difference between an MCP server and an API? Your API is what your product already exposes to developers. An MCP server is a thin layer in front of it that describes a short list of tools in a way AI apps such as ChatGPT and Claude understand, and calls your API when the AI uses one.

### Is a ChatGPT plugin the same as a Claude connector? Close. Both are built on an MCP server. OpenAI's docs call the published package a plugin (it can also hold skills), and Claude calls an added MCP server a connector. One remote MCP server can serve both, but each directory has its own submission and review.

### Do I need OAuth for my MCP server? Only if tools act on a person's account. Public, read-only data can use no sign-in. For signed-in tools, ChatGPT and Claude both expect OAuth, and ChatGPT's portal doesn't accept API keys for public submissions.

### Is HTTP with SSE still supported? It has been deprecated since the 2025-03-26 MCP spec. Some AI apps still accept it for older servers, but new remote servers should use Streamable HTTP.

### Do I need to build a widget or MCP App? No. Interfaces are optional. An app can offer tools only, and ChatGPT and Claude show the results in the chat.