AI Quick Hit - Model Context Protocol a key development of interoperability in AI growth

The Model Context Protocol (MCP) is like a universal connector for AI systems, similar to how a USB-C port works for devices. It was created by Anthropic to make it easier for AI tools to connect to different data sources and tools without needing separate, complicated setups for each one.

Here’s a simple explanation of MCP and why it’s important:

What is MCP?

MCP is a set of rules (a "protocol") that helps AI systems, like chatbots or assistants, talk to other tools and data sources. Think of it as a universal language that both the AI and the tools understand. Instead of building custom connections for every tool or database, MCP provides a single, standardized way to connect everything.

For example:

• Without MCP: If you want your AI to access Google Drive, Slack, and your company database, you’d need separate connections for each.
• With MCP: You just use MCP as the bridge, and the AI can access all these tools through one system.

How Does MCP Work?

MCP uses two main pieces:

1. Servers: These are programs that hold data or provide tools. For instance, a server might give weather updates or store files.
2. Clients: These are the AI systems (like chatbots) that use the servers to get information or perform tasks.

When you ask an AI assistant something, like "What’s the weather in New York?" the assistant uses MCP to find the right server (a weather tool) and get the answer.

Why is MCP Useful?

1. Simplifies Connections: Instead of creating separate setups for every tool or database, MCP acts as a single connection point.
2. Keeps AI Updated: Many AI systems are trained on old data. With MCP, they can access live information from tools like Google Drive or Slack.
3. Saves Time: Developers only need to build one connection using MCP instead of many custom ones.
4. Works Across Systems: Just like USB-C works with many devices, MCP works with many tools and databases.

Real-Life Example

Imagine you’re running a pizza delivery app. Without MCP, you’d need to write special code for every AI assistant (like GPT-4 or Claude) to let them order pizzas from your system. With MCP, you only set up one connection, and all assistants can use it easily.

Why Does This Matter?

MCP makes AI more powerful and useful by giving it better access to real-world data and tools. For businesses, it means faster workflows and smarter assistants. For people, it means AI that’s more helpful in everyday tasks.

In short, MCP is helping AI become more connected and capable!

Citations:

1. https://workos.com/blog/model-context-protocol
2. https://norahsakal.com/blog/mcp-vs-api-model-context-protocol-explained/
3. https://www.anthropic.com/news/model-context-protocol
4. https://modelcontextprotocol.io/introduction
5. https://www.seangoedecke.com/model-context-protocol/
6. https://www.youtube.com/watch?v=MC2BwMGFRx4
7. https://nshipster.com/model-context-protocol/
8. https://docs.anthropic.com/en/docs/agents-and-tools/mcp