How Anthropic's MCP Baits Software Engineers
Nerd Sniping to Drive Curiosity
Before we get into how Anthropic introduced MCP, I want to look at a pattern I’ve seen over and over since 2016.
Something simple, sticky, and crafted to subtly command attention.
Studies show that 90% of people can’t solve this problem.
🍎 + 🍎 = 6
🍎 + 🍌 = 7
🍌 - 🥝 = 2
🥝 + 🍎 + 🍌 = ❓
Little known fact: hundreds (maybe thousands) of studies have been done to confirm if people can do basic algebra with fruit emojis.
Okay, no they don’t. Nobody is funding peer-reviewed fruit math. But the premise seems to exist in endless supply.
You tend to see these little logic puzzles on Facebook or WhatsApp, designed to freeze your scroll just long enough to pull you in. They don’t have a prize or a purpose. The only reward is proving to yourself that you’re smart enough to solve it.
This trick actually has a name: nerd sniping.
The term comes from an xkcd comic, and the idea is simple: show a nerd a solvable problem and they’ll drop everything to work on it. It’s like an attention trap, engineered specifically for the problem-solving brain.
You don’t necessarily need to be a physicist, software engineer, or researcher to be nerd sniped. You don’t really even need to be a nerd. All you need is conviction that you’re capable and be willing to spend a few minutes of time proving it.
Circling back: MCP as a Nerd Snipe
In late 2024, Anthropic announced the Model Context Protocol (MCP), a framework for building servers that define how AI agents can interact with external tools and resources. Think of it like a user manual that teaches agents like Claude to use your app.
MCP fascinates me. Not necessarily for what it does, but for how it was released.
This wasn’t a high-profile launch.
Instead, details about MCP were quietly released in an announcement post.
In this post, they detail a few components:
Local MCP server support in the Claude Desktop apps (Anthropic)
The Model Context Protocol specification and SDKs (Github)
An open-source repository of MCP servers (Github)
The first link directs readers to download the Claude desktop app. The other two link to Github, seemingly as a nod to developers and the open source community.
Interestingly, the second link doesn’t even contain code, it’s a markdown file with diagrams, higher-level explanations, and links to their docs.
And if you wanted to try out an MCP server now, you would need to take the following steps:
Clone the Github MCP Server sample repo
Go into Settings > Developer > Edit Config
Open the config file in a text editor e.g. Sublime Text
Add the server by name to a JSON object
None of these steps are particularly difficult, or even all that technical.
In fact, most MCP server samples are no more complex than a basic API.
With little lift, a dev can learn and apply MCP in a few hours. That’s what makes it so compelling.
Anthropic created a challenge engineers can’t resist.
It’s nerd sniping at scale.
Rather than framing this like a new feature, they’ve tapped into developer instinct: piquing their curiosity, and galvanizing their urge to build.
No launch event. No marketplaces. No ad spend.
And it has been very effective. Anecdotally, this rollout was successful in capturing the cultural mindshare of the developer community.
I’ve heard topics like this discussed in standup meetings, networking events, and casual conversations with engineers. Many of my friends have mentioned that their startup plans to build an MCP server soon. It seems to have caught the industry’s imagination.
If you go to Github, try querying "model context protocol" in:readme.
Like those fruit puzzles, Anthropic’s release of MCP draws in a specific kind of person: the kind who can’t resist making sense of something opaque, modular, and unsolved.
It’s a soft power play: define the structure of the AI agent landscape, and let the developers bring it to life.
P.S. 🥝 + 🍎 + 🍌 = 9 (but you knew that, right? 😉)