Apparently MCP is like a universal translator between your AI model and the real world.
The model knows what to talk. But it doesn’t know how to talk to.
MCP fixes that.
An MCP server is a lightweight program that sits between your LLM and your tools.
Like a smart plug adapter.
It lets the model call APIs, search databases, fetch customer info, trigger workflows. And you don’t need to hardcode every connection.
Instead of wiring every tool manually, you build once for the MCP.
The model uses plain language to trigger functions.
Example;
Imagine you’ve hired a cyborg assistant. But it’s blindfolded and can’t touch anything. MCP is what lets them say, “Hey, turn on the lights” and the smart home responds.
Or think of MCP like a USB-C port for your AI. Just like USB-C lets you connect any device to any charger or monitor without fuss, MCP lets your AI plug into any tool or data source seamlessly.
Same model. Suddenly way more useful.
Examples of what this looks like:
The model says, “Show me this customer’s open tickets.” MCP calls your support tool API and returns a list.
The model says, “Calculate ARR for these ten accounts.” MCP fetches revenue data from your CRM and runs the math.
The model says, “Start the incident workflow and notify engineering.” MCP triggers the webhook and fires off Slack messages.
No magic. Just a clean, structured way to let models do real work inside your stack.
How is MCP different from Zapier or Make or n8n
Zapier, Make, and n8n are automation tools. You define the steps. They execute with clockwork precision. Deterministic. Safe. That matters.
MCP isn’t that. At least not yet.
You can’t plug Claude desktop directly into Make or Zapier and say “build me a lead scoring pipeline.”
Not today.
MCP right now needs a local or hosted machine running the server. It needs you to set up the bridge. That’s where tools like Anthropic’s Computer Use come into play.
What MCP gives you is live agency. The model sees context, makes a call, gets a response, decides next steps. It’s not bound to a flowchart. It’s doing light orchestration in real time.
So right now, they complement each other. You use automation tools for structure. You use MCP for reasoning.
Eventually? Someone’s going to ship an agent layer that writes and executes the flows inside Make or n8n. All from a prompt.
Then things get interesting.
MCP today is a whisper of that future. One where you won’t need to build workflows.
The model will.
And they’ll run like scripts.
Until then, keep one eye on it.
It’s not just tooling.
It’s a new runtime for decision making.
And yeah, MCP stands for Model Context Protocol.
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