What is MCP? MCP, the Model Context Protocol, is an open standard that lets an AI app such as Claude or ChatGPT connect to outside tools and data: your database, your analytics, your calendar. Anthropic released it in November 2024.
What does MCP mean in AI, in plain words?
An AI assistant is good at language but blind to your own systems. It has never seen your customer table, your Google Search Console account or your App Store reviews. MCP is the agreed way for an assistant to ask a tool "what can you do?" and then use it.
The official documentation describes it as a USB-C port for AI applications. One standard plug replaces a drawer of different cables. Any AI app that speaks MCP can use any tool that speaks MCP, with no custom work between the two. That analogy is the only one you need.
Why was MCP created? Before MCP, every pairing was a custom job. Connecting Claude to a database was one integration. Connecting ChatGPT to the same database was another. With N AI apps and M tools you end up maintaining N times M connectors, and each breaks on its own schedule.
MCP turns that into N plus M. Each app learns the protocol once, as a client. Each tool is wrapped once, as a server. Anthropic announced it on November 25, 2024, as an open-source standard, in Introducing the Model Context Protocol. Because it is open, anyone can build on it without asking permission.
If you want the short dictionary entries, see Model Context Protocol and MCP server. This article covers how it all fits together and what you can do with it today.
What can you do with MCP?
MCP matters most when you stop pasting data into a chat and let the assistant fetch it. Here are four things people do with it, and none of them needs code.
- Ask your own database a question. Connect a PostgreSQL server to Claude and ask "how many customers signed up last week?" The assistant reads your table names, writes the query, runs it and answers in plain English. The full walk-through is in query Postgres from Claude.
- Bring Search Console data into ChatGPT. Ask which pages lost clicks this month and the assistant pulls the numbers itself. See Search Console data in ChatGPT.
- Check search interest. A Google Trends server lets the assistant compare terms and regions without you opening a browser tab.
- Read and manage app data. An App Store Connect server lets the assistant look at your apps, TestFlight builds and reviews, and a WhatsApp server lets it read chats and send messages when you allow it.
The pattern is the same each time. You ask in normal language, the assistant picks a tool, the tool returns real data, and the assistant explains it. You can see this in action in ask your database in plain English.
How does MCP work: hosts, clients, servers and where they run?
MCP has three parts. Developers use these words, and they are easy to learn.
- Host: the app you actually use, such as Claude, ChatGPT, Claude Code or Cursor.
- Client: a connector inside the host. Each client keeps one connection to one server. See MCP client.
- Server: the program that does the real work, such as running a query or calling an API. See what an MCP server is.
A server can offer three kinds of things. Tools are actions the AI can take, like running a query. Resources are data it can read, like a file. Prompts are reusable templates. Tools are what most people care about, and they are also where safety decisions live.
When you connect, the client asks the server for its list of tools, along with a description of each one. The model reads those descriptions, decides which tool fits your request and calls it. The server runs it and sends the result back. Underneath, the messages use JSON-RPC 2.0, and you only need to know that if you build or debug servers. The architecture overview on modelcontextprotocol.io has the formal version.
A server also runs in one of two places, and each uses its own transport.
- On your computer, over
stdio. Your AI app starts the server as a background process. This suits a tool that touches your own files. You install and update it yourself, and it only works on that machine. - On a server elsewhere, over Streamable HTTP. The server lives at a URL and your app connects to it over the network. Web apps like Claude.ai and ChatGPT can only use this kind, because they cannot start programs on your laptop.
That last point is why remote servers matter for non-developers. If you live in a browser-based assistant, you need a remote server. Read remote MCP server for more.
MCP keeps evolving, and the specification is versioned by date. If you only use servers, your AI app and the server settle the version between them. If you build servers, the latest specification is on modelcontextprotocol.io and our summary of MCP spec changes is a good starting point.
Who supports MCP?
Support spread well beyond Anthropic. The table shows where MCP is available as of October 2026. Check each vendor's docs before relying on a specific feature, because setup steps and plan limits change.
AppMCP supportWhere to start
Claude (web and desktop)
Remote servers as custom connectors
ChatGPT
Remote servers through connectors
Claude Code
Local and remote servers
Cursor
Local and remote servers
VS Code with Copilot
Local and remote servers
OpenAI documents its MCP support in the OpenAI API guide to MCP servers, and Anthropic explains custom connectors in its help centre. For a longer, maintained list, see which AI clients support MCP.
How is MCP different from an API or function calling?
All three end with an AI doing something outside the chat, so people mix them up. An API is one service's own interface. Function calling is how one model provider lets you describe functions to its model. MCP is a shared protocol between any AI app and any tool, so the tool is described once and found automatically.
MCP does not replace APIs. Most MCP servers wrap an existing API or database driver. Our comparisons go deeper: MCP vs API and MCP vs function calling.
Is MCP safe to use?
MCP standardizes how an AI talks to a tool. It does not make the tool safe. Researchers have shown real problems since 2025:
- Prompt injection: text returned by a tool tricks the AI into doing something you did not ask for.
- Tool poisoning: a malicious server hides instructions in its tool descriptions.
- Over-broad access: an assistant with write access to a database can change data if it is told to, or tricked into it.
The fix is least privilege. Give the AI only the tools the task needs, keep anything that writes or deletes switched off until you need it, and only connect servers you trust. The protocol's own security best practices say the same. For depth, read the MCP security checklist, the MCP security guide and prompt injection through MCP tools.
How do you start with MCP in five minutes, without installing anything?
You do not need Node, Python or Docker. A hosted server runs on someone else's machine and you connect to it by URL. This is what MCPifex does. You pick a server, save your own credentials, choose which tools are allowed, and get one URL and API key. Write tools, such as the PostgreSQL execute tool, start off. You turn them on only if you want them.
- Create a free account. The free plan covers 3 MCP instances and needs no card.
- Pick a server from the marketplace, for example PostgreSQL or Google Search Console.
- Follow the four portal steps: name the instance, add connection settings, choose what is allowed, get connected.
- Paste the URL into your assistant. Setup for Claude and ChatGPT is a few clicks. The quickstart shows every screen.
- Ask a real question about your data and watch which tool the assistant calls.
Developers who prefer a local setup can run an open-source server themselves. It is free, and the trade-off is that you install, update and secure it.
Key takeaways
- MCP is an open standard that lets any AI app use any tool through one shared protocol.
- A host app runs one client per server, and each server exposes tools, resources and prompts.
- Servers run on your machine over
stdioor remotely over Streamable HTTP. Web assistants need remote ones. - MCP does not make a tool safe. Allow only the tools a task needs.
- You can try it in minutes with a hosted server and nothing to install.
Frequently asked questions
In AI, MCP stands for Model Context Protocol, an open standard that lets AI apps connect to outside tools and data through one shared method. Anthropic announced it in November 2024. An assistant that supports MCP can discover a tool's abilities and use them without custom code for each pairing.
No. A REST API is one service's own interface that you integrate by hand. MCP is a protocol that standardizes how any AI app discovers and calls any compliant server's tools. An MCP server is often a thin wrapper around an existing API.
No. If your assistant supports remote MCP servers, you can paste a server URL into it. A hosted service such as MCPifex runs the server for you, so you install nothing and never edit a config file.
The protocol does not guarantee safety. Prompt injection, tool poisoning and over-broad access are real risks. Allow only the tools a task needs, keep write and delete tools off by default, and connect only servers you trust.
Anthropic created MCP and released it as open source on November 25, 2024. Claude, ChatGPT, Claude Code, Cursor and VS Code with Copilot all support MCP servers, with different setup steps in each.
Sources
- Model Context Protocol, "What is the Model Context Protocol (MCP)?"
- Model Context Protocol, "Architecture overview"
- Anthropic, "Introducing the Model Context Protocol", November 25, 2024.
- OpenAI, "MCP servers", OpenAI API documentation.
- Anthropic, "Get started with custom connectors using remote MCP".
- Model Context Protocol, "Security best practices".
Ready to try it?
Run hosted MCP servers behind one endpoint and choose exactly which tools your AI can use.