Before USB, every device had its own proprietary connector. Printers used parallel ports, keyboards used PS/2 connectors, cameras used serial cables. Connecting a new device to your computer meant finding the right cable, installing a specific driver, and hoping for compatibility. USB standardized all of that into one universal port. The Model Context Protocol does the same thing for AI.
Anthropic introduced MCP in November 2024 as an open standard for connecting AI systems to data sources and tools. As documented on Wikipedia, MCP was later donated to the Agentic AI Foundation under the Linux Foundation in December 2025, with co-founding support from Anthropic, Block, and OpenAI, making it an industry-wide standard.
The problem MCP solves is integration fragmentation. Before MCP, connecting an AI agent to your CRM required custom code. Connecting it to your email required different custom code. Connecting it to your accounting software required yet another integration. Every tool needed its own bridge, and every bridge had to be built and maintained separately. For a 10-person business using 8 different software tools, that meant 8 separate integrations, each with its own failure points.
MCP standardizes these connections. An AI agent that speaks MCP can connect to any tool that also supports MCP through a single, consistent interface. The protocol defines three core primitives: tools (actions the AI can take), resources (data the AI can read), and prompts (structured instructions the AI can follow). Any application that implements these primitives becomes instantly accessible to any MCP-compatible AI system.
For business owners, MCP matters because it dramatically reduces the cost and complexity of AI integration. Without MCP, adding a new tool to your AI system means hiring a developer to build a custom connector. With MCP, the connection is standardized, like plugging in a USB device. This makes it faster to deploy AI agents and easier to swap or upgrade individual tools without rebuilding the entire system.
MCP also makes AI systems more portable. If you start with one AI provider and want to switch to another, MCP means your integrations carry over. You are not locked into a vendor because of proprietary connectors. The open-source nature of the protocol ensures no single company controls it.
At DeployLabs, we build AI business engines using MCP as the integration backbone. When your agents need to read data from your CRM, send messages through your email platform, or update records in your accounting system, MCP provides the standardized connection layer. For more on how AI systems connect to business tools, see our guide to AI operating systems.