MCP stands for Model Context Protocol. It is an open standard, introduced by Anthropic in late 2024, that defines how an AI (artificial intelligence) application connects to external systems: databases, documents, or software tools. It operates on a client-server model: the AI assistant is the client, and each system that wants to share data or actions exposes an MCP server.

Why does it matter?

Without a standard, every connection between an AI and a system requires custom integration. MCP proposes a common approach to this, similar to how a universal port works with devices. This way, a single server can work with different assistants that support the protocol.

• More context: AI can access real-world data rather than responding solely based on what it learned during training.
• Greater control: The server determines what information and actions are available, and with what permissions.
• Less friction: You can work with your data right from the AI tool you already use, without switching screens.

MCP doesn't make an AI smarter. It provides structured access to information and tools. The quality of the result still depends on the data and how you use it.

Story mode

Martín works in marketing for an online home decor store and uses an AI assistant every day to write copy. He connects that assistant to his store’s customer data via MCP. Now, without leaving the conversation, he asks how many customers have made two purchases this month and requests a draft message for them.

How to Use It with Data4Sales

With Data4Sales on ChatGPT and Claude, you can bring your data into the AI tools you already use, via MCP. This allows you to view consolidated customer information directly from those assistants. If you prefer to work within the platform, Orbis offers these capabilities with the full context of your business.

Related terms

• Context-Aware AI
• Orbis
• AI Agent
• Data Sources