MCP, the Model Context Protocol, is an open standard that lets AI assistants connect to outside tools and data in one consistent way. Anthropic introduced it in late 2024, and it has since been adopted by many AI apps and developer tools. If you’ve heard people say an AI “has an MCP server for” something, this guide explains what that means.
The problem MCP solves
An AI model on its own can only work with the text you give it. To be useful in real work, it needs to read files, query a database, check a calendar or update a website. Before MCP, every AI app had to build a custom integration for every tool, and every tool maker had to build one for every AI app. That is a lot of duplicated work.
MCP is a shared plug standard. A tool builds one MCP server, and any AI app that supports MCP can use it. A common comparison is USB-C: one connector that works across many devices.
How MCP works
MCP has three parts:
- Host or client. The AI app you use, such as a chat assistant or a coding tool. It decides when to call a tool.
- Server. A small program or web endpoint that exposes a tool’s abilities, such as “list posts” or “create file”.
- The protocol. The agreed message format between them, built on JSON-RPC. Servers can run locally on your machine or remotely over HTTP.
A server can offer three kinds of things:
- Tools. Actions the AI can perform, like sending a message or updating a record.
- Resources. Data the AI can read, like documents or database rows.
- Prompts. Reusable templates for common tasks.
A simple example
Say you ask your AI assistant, “Which of my blog posts are still drafts?” With an MCP server for your website connected, the assistant sees a “list posts” tool, calls it with a status filter, gets the results back and answers in plain language. You never open the dashboard. Ask it to publish one, and it calls a different tool.
What MCP is used for
- Software development. Coding assistants reading repositories, running tests and querying databases.
- Content and websites. Creating and editing pages, posts and media through chat. See WordPress MCP servers.
- Business tools. Looking up CRM records, searching documents, checking analytics.
- Personal productivity. Email, calendar and notes assistants.
MCP vs an API
An API is how software talks to a specific service. MCP sits on top: it describes a service’s abilities in a standard form that an AI can discover and use without custom code. The AI can ask the server what it can do, then decide which tool fits the request. Under the hood, an MCP server usually calls regular APIs.
Is MCP safe?
MCP gives an AI real power, so access control matters. Good practice includes:
- Least privilege. Give a server only the permissions the task needs.
- Revocable credentials. Use tokens you can cancel at any time.
- Human approval for risky actions, such as deleting data or spending money.
- Trusted servers only. Treat an MCP server like any software you install. Content it returns should not be trusted blindly either.
How to get started
- Pick an AI app that supports MCP, such as a desktop assistant or a coding tool.
- Find an MCP server for the tool you want to control.
- Add the server’s address or command and credentials in the app’s settings.
- Ask the assistant to do something small and read-only first, like listing items, before letting it make changes.
For a hands-on example, see how to connect Claude Code to WordPress.
Model context protocol FAQ
Who created MCP?
Anthropic introduced it as an open standard in November 2024. Other AI companies and tool makers have since added support.
Do I need to code to use MCP?
Not to use one. Connecting an existing server is mostly configuration. Building your own server takes some programming.
Is MCP only for Claude?
No. It is an open protocol, and many AI apps and developer tools support it.