What is an MCP server?
And how it differs from a plugin and an API.
An MCP server is a program that exposes tools and data to an AI client over the Model Context Protocol — an open standard that Claude, ChatGPT, and Cursor all support — so the AI can call those tools directly and take real actions instead of only describing them.
MCP (Model Context Protocol) was introduced by Anthropic as an open way to connect AI clients to external systems. A server declares the tools it offers — query a database, read a file, call an API, search the web — and the client calls them when a task needs them. Because the protocol is shared, one server works across every compatible client. You find and connect servers through an MCP server marketplace.
What does an MCP server do?
An MCP server gives an assistant capabilities it does not have on its own. In practice a connected server can:
- Query a database or data warehouse and return structured results.
- Read and write files — spreadsheets, documents, structured data.
- Call an external API to fetch or update data on your behalf.
- Search the web or a knowledge base and hand back sources.
- Run a multi-step workflow — the model calls several tools in sequence.
The model decides when to call each tool; the server decides what each tool does. That split is what makes a connected assistant able to act.
MCP vs plugin vs API
These three often get conflated. The difference is who the interface is for and how portable it is.
| Dimension | MCP server | Plugin | API |
|---|---|---|---|
| Who uses it | The AI client, at run time | The AI client, inside one host | A developer, in code |
| Portability | Any MCP client — Claude, ChatGPT, Cursor | One host only | Anywhere, but needs custom wiring |
| Tool discovery | Self-describing — advertises its tools | Host-defined manifest | None — you read the docs |
| Standard | Open Model Context Protocol | Vendor-specific | Per-service, no shared standard |
| Setup for non-developers | Connect over a URL, no code | Enable inside the host | Requires a developer |
The short version: an API is for programmers, a plugin is for one host, and an MCP server is for the AI itself to use — anywhere the protocol is supported.
How MCP servers work with Claude, ChatGPT, and Cursor
All three clients speak the Model Context Protocol, so you connect a server once and use it in whichever one you have open. There are two paths:
- Hosted — the server runs on infrastructure someone else operates. You point your client at a remote URL and sign in; nothing installs on your machine. This is the path that reaches ChatGPT and mobile clients.
- Local — the server runs on your own machine over stdio. You add it to your client's configuration and it runs where your files are — good for offline and development use.
Frequently asked questions
- What is an MCP server in simple terms?
- An MCP server is a small program that gives an AI assistant a set of tools and data to work with. It speaks the Model Context Protocol — an open standard — so any compatible client (Claude, ChatGPT, Cursor) can call its tools. Connecting one turns a chat assistant into something that can take real actions, like querying a database or managing files.
- What is the difference between MCP and a plugin?
- A plugin is built for one host application and only runs inside it — a ChatGPT plugin works in ChatGPT and nowhere else. An MCP server is host-agnostic: it implements the open Model Context Protocol, so the same server connects to Claude, ChatGPT, or Cursor without being rewritten. Plugins lock you to one vendor; MCP servers are portable.
- What is the difference between MCP and an API?
- An API is a raw interface a developer wires into code. An MCP server wraps capabilities so an AI client can discover and call them directly — it advertises its tools, their inputs, and their descriptions in a shape the model understands, then handles the calls. In short: an API is for programmers; an MCP server is for the AI itself to use at run time.
- How does an MCP server work with Claude, ChatGPT, and Cursor?
- Each of those clients supports the Model Context Protocol, so you connect a server once and it works across them. A hosted server connects over a remote URL you point the client at; a local server runs on your machine over stdio. Once connected, the client can call the server’s tools whenever a task needs them.
- Do I need to be a developer to use an MCP server?
- No. Connecting a hosted MCP server from a marketplace is a guided, no-code step: you point your AI client at a URL and sign in. You only supply your own credentials when a specific server needs them to do its job — that is configuration, not coding.
- Where do I find MCP servers?
- You find MCP servers in an MCP server marketplace or directory, where they are grouped by use case with descriptions and connection details. FindAgent hosts a directory of MCP servers and cross-LLM agents you can connect to Claude, ChatGPT, or Cursor.
Related
Browse the live MCP server directory on FindAgent, or browse the marketplace.