Model Context Protocol is Quickly Becoming the USB of an AI-First Developer Experience

I'd like to start by saying that the AI-First developer experience ecosystem is really heating up. It’s getting super competitive and products are jockeying for market share (which there is obviously quite a bit to be had). The entire landscape of tools has changed in the past six months as new capabilities are being matched with state-of-the-art LLM’s, bringing a ton of potential and new ways of working closer than ever.

And, despite technology changing almost day-to-day, some patterns are starting to emerge as potential new standards. A pretty impressive example of this is the “Model Context Protocol” (or MCP). While this post and opinion might sound like more technical jargon at first, I believe we'll see MCP quickly become the de-facto USB-like connection between AI tools and just about everything else.

Claude can now order your groceries...

So what is the Model Context Protocol and why should you care?

MCP is an open standard developed by Anthropic that acts like a universal connector - like I mentioned, similar to USB, but for AI tools. Its primary purpose is to (seamlessly) link AI models to external data sources, tools, and systems without the headache of custom, one-off integrations. It might connect to a database, pull from an API, or access internal documentation, via a “plug-and-play” type of interface.?Really that's up to your implementation.

Example MCP Architecture:

MCP servers typically provide three main functionalities:

1. Prompts: Pre-defined templates or instructions to guide AI interactions
2. Resources: Structured data or content that provides context to the AI model
3. Tools: Executable functions that allow AI models to perform actions or retrieve information

The benefit of MCP is to eliminate struggling with fragmented setups and reinventing the wheel every time you'd like your AI applications to talk to a new system. Today, this is starting to become important to AI engineers and anyone using AI-first tools. That means sooner than later we should expect it to make its way into more mainstream workflows.

Why MCP Matters in the AI-First Developer Race

AI developer tools are improving very rapidly, and MCP specifically appears to be an early standard that we can find some common ground on. Several AI-enabled IDEs and developer tools like Cursor, Windsurf, Cline for VSCode, and Claude Desktop are all supporting MCP. (Claude Desktop is not an IDE but shows how MCP can work for more than just developers).

These tools are leveraging MCP to streamline software development workflows, allowing developers to focus on building innovative solutions instead of spending too much time working on the integration between tools. MCP is also open-source, meaning it’s not locked behind a single vendor; it’s a community-driven standard and that will help it gain more traction and wider adoption.

There are already marketplaces and repositories of open source MCP integrations:

• Open Source Server Repository: https://github.com/modelcontextprotocol/servers
• MCP Server "Marketplace": https://www.mcp.run/

Examples of some MCP integrations (the list is growing daily):

1. Google Drive - Enables file access and search within Google Drive, allowing AI models to retrieve, organize, and process documents stored in the cloud
2. GitHub - Supports repository management, file operations, and GitHub API integration, allowing AI models to interact with code repositories, issues, and pull requests
3. GitLab - Offers GitLab API integration for project management, enabling AI models to manage repositories, issues, and merge requests on GitLab

Here's a few mentions of what this looks like in the wild:

• Stripe released an MCP server allowing for direct integration with their APIs:

• Claude connecting to Amazon Fresh to order groceries:

• Discussions about driving toward standards and where this technology will go next:

What's next?

There's a ton of information and new use cases coming out daily at this point so don't hesitate to go check it out for yourself. I'm really looking forward to seeing how MCP could take off. If you're an engineer or a technology leader, take time to do some research and look into how it could help you become more productive or how it could assist in your next AI engineering project. If you're interested in chatting about this or any emerging AI-first software accelerators, feel free to reach out and connect!