What's the Difference Between MCP and AI Agent? - Atricore

As AI capabilities expand into enterprise environments, two terms keep coming up: MCP (Model Context Protocol) and AI Agent. While they’re related, they serve different purposes. Understanding the distinction helps you make better technology decisions.

What is MCP?

Think of MCP as a universal USB-C cable for AI. Developed by Anthropic, the Model Context Protocol connects applications and systems with language models—without the need to build custom APIs or integration code for each connection.

MCP provides a standardized way for AI systems to:

Access data from various sources
Execute operations in connected systems
Maintain context across interactions

The protocol works with multiple language models including Claude, ChatGPT, Gemini, and Llama. It’s an open standard designed for interoperability.

MCP Server Example

A Wazuh MCP Server connects your SIEM system with an AI assistant. The AI can query security events, analyze alerts, and provide insights—all through the standardized MCP interface. The server handles authentication, data formatting, and API translation.

What is an AI Agent?

An AI Agent is a more sophisticated entity that may utilize one or multiple MCP Servers. Agents operate with greater autonomy, executing actions, making decisions, and automating processes across your environment.

Key characteristics of AI Agents:

Can operate with or without chat interfaces
Execute multi-step workflows
Make decisions based on pre-configured rules
Take actions on your behalf

AI Agent Example

A security operations AI Agent might monitor alerts from your Wazuh MCP Server, correlate them with threat intelligence from another MCP Server, create tickets in your ITSM system, and notify the appropriate team—all automatically based on rules you’ve defined.

The Key Distinction

An MCP Server is the bridge. It connects an app or system with a language model through a defined interface. It’s the connection layer that makes data and capabilities accessible.

An AI Agent leverages bridges to act. It can use multiple MCP connections to operate autonomously, designed to take actions on your behalf based on pre-configured rules and decision logic.

When to Use Each

Use MCP Servers When:

You want to make a system accessible to AI assistants
You need standardized data access without custom integration work
You’re building conversational interfaces to existing tools
You want humans in the loop for all decisions

Use AI Agents When:

You need autonomous operation without constant human input
Workflows span multiple systems and data sources
Decisions can be made based on defined rules
Speed of response matters more than human review

Building Your AI Strategy

Most organizations will use both. MCP Servers provide the connectivity layer—making your security tools, identity systems, and business applications accessible to AI. AI Agents build on that foundation to automate workflows and reduce manual work.

At Atricore, we develop both MCP Servers for security and identity platforms and AI Agents that leverage them for autonomous security operations.