When an AI assistant creates a blog draft or checks a database, several pieces of software work together. APIs and MCP servers play different roles in that process. Understanding the difference makes AI automation much easier to follow.

An API, short for Application Programming Interface, defines how software can interact with another component or service. It specifies available operations, required inputs, and expected results. APIs exist in many forms, including web services and software libraries. MDN’s API overview

For example, the WordPress REST API lets authorized software create posts, retrieve content, and change a post’s publication status. A program sends a request containing details such as the title and article body, and WordPress returns a response. WordPress posts API

An MCP server is a program that implements the Model Context Protocol. It gives compatible AI applications a standard way to discover and access capabilities. Those capabilities can include tools that perform actions, resources that supply information, and reusable prompt templates. MCP server concepts

In our blog setup, the MCP server exposes tools with names such as create_draft, get_post, and publish_post. Their descriptions and input definitions help the assistant understand which tool fits the request.

Here is how the pieces work together:

1. You ask the assistant to draft a blog post.
2. The assistant prepares the content and selects the appropriate tool.
3. The AI application sends the tool call through its MCP client.
4. The MCP server translates that call into a WordPress API request.
5. WordPress saves the draft and returns its ID.
6. The result travels back to the assistant.

The API performs the website operation. The MCP server provides a standardized connection between that operation and the AI application. MCP servers can run locally or remotely. MCP architecture

The main difference is scope. API is a broad term for a software interface. MCP is a specific protocol, and an MCP server implements it. They are complementary technologies, rather than competing replacements.

An MCP server also does not have to call a web API. It might read local files, query a database, or perform calculations directly. Likewise, an AI application can use APIs without MCP if developers build the integration themselves.

MCP standardizes the connection, but developers still need to implement the underlying actions and respect access permissions. In our publishing workflow, the assistant writes the article, the MCP server exposes the publishing tools, and WordPress stores and publishes the content.