MCP stands for Model Context Protocol. In simple terms, it gives AI applications a common way to connect to outside systems like files, databases, search tools, or business apps, instead of every product inventing a different connector for everything.
Anthropic introduced MCP as an open standard, and the official documentation now describes it as a way for tools like Claude or ChatGPT to connect to data sources, tools, and workflows. That is why people compare it to USB-C for AI: one interface, many connections.
Why it matters
- It reduces one-off integration work.
- It makes agent workflows more portable across products.
- It gives teams a cleaner way to expose internal systems to AI tools.
- It helps non-technical users get richer workflows through products that already support MCP.
What it looks like in practice
Imagine an AI assistant that can read a design file, fetch product data from a catalog, search company documentation, and write the result into a task tracker. MCP does not make the assistant smart by itself. It makes the connections more standardized.
Why non-technical users should care
The practical effect is simple: better connected AI tools can do more with less copy-pasting. That means fewer brittle browser hacks, fewer manual exports, and more workflows that feel like real software instead of a chat box pretending to be software.
Risks and limitations
- More connections mean more security questions.
- A bad tool integration can still return bad data.
- Standardization does not remove the need for permissions, logging, and human review.
- MCP helps with connectivity, not judgment. You still need the right workflow and the right model.
Why adoption matters
The MCP ecosystem has matured fast enough that the maintainers are already publishing specification release candidates and governance updates. That is a sign the protocol is moving from novelty toward infrastructure.
Dera’s view
MCP is useful because it lowers friction, but it is not the product. The product is the workflow outcome. Dera’s job is still to help people choose which connected AI tool is actually worth trusting for a given task.