Cloud & Infrastructure
MCP vs. API
Also known as: Model Context Protocol, Application Programming Interface
APIs define how software communicates with software. MCPs (Model Context Protocol) let AI models connect to tools directly — no custom integration code needed.
An API — Application Programming Interface — is a defined way for one piece of software to communicate with another. When your application retrieves data from Salesforce, or your website shows live inventory, it's using an API. APIs are designed for machines: they require developers to write code that properly formats requests and handles responses.
An MCP — Model Context Protocol — is a newer standard developed by Anthropic that allows AI models to connect to external tools and services in a standardized way. Think of it as a universal adapter that lets an AI assistant interact with your calendar, your email, your CRM, your network monitoring platform — anything that has published an MCP server.
The practical difference: APIs require custom integration code. MCPs let AI models consume capabilities directly. If Slack publishes an MCP server, any MCP-compatible AI assistant can read messages, post updates, and search history — without a developer writing a custom integration.
For organizations thinking about AI integration, MCPs dramatically lower the friction of connecting AI to existing systems. The ecosystem is still early, but the direction of travel is clear.