Imagine a world where software tools, APIs, and even documentation could understand not just what you want, but the context in which you want it. That’s the promise of the Model Context Protocol (MCP)—a new way for software to communicate, share, and reason about information. In this post, we’ll break down what MCP is, why it matters, and how its core ideas—model, context, and protocol—work together to unlock new possibilities for developers and users alike. Let’s start by understanding why MCP was introduced in the first place.
Why Was MCP Introduced?
MCP was created because users wanted to ask AI chat agents like ChatGPT or Claude about their own data—like sales numbers or support tickets—but these agents couldn’t access that information directly. For example, if you asked an AI, “How many orders did we ship last week?” it wouldn’t know, because there was no standard way to describe or share your data securely. This gap highlighted the need for a new approach to data sharing and interaction.
Anthropic introduced MCP to solve this. Instead of giving AI agents full access to your systems, MCP lets you describe what data you have and how it can be used, in a way the AI can understand—without exposing everything. This makes it possible for chat agents to answer questions and automate tasks using your data, while you stay in control. Now that we’ve seen the motivation, let’s look at what MCP actually is.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is a standard for describing, sharing, and exchanging information between software systems in a way that’s both structured and context-aware. MCP isn’t just about moving data from point A to point B—it’s about making sure that data is meaningful and actionable in the right context. To understand how MCP works, let’s break down its three key concepts: model, context, and protocol.
What is a “Model” in MCP?
A model in MCP is a structured representation of something—think of it as a schema. Models define the shape and meaning of data so that different systems can understand and work with it. This is the foundation for clear communication between tools.
Example Model:
Suppose you’re building an API for a book library. Your “Book” model might look like this:
{
"title": "The Pragmatic Programmer",
"author": "Andrew Hunt, David Thomas",
"isbn": "978-0201616224",
"published_year": 1999
}This model tells any system what a “Book” is and what information it contains. But a model alone isn’t enough—context is just as important.
What is “Context” in MCP?
Context is the information that surrounds a model and gives it meaning in a specific situation. Context helps software understand not just what data is, but how and why it’s being used. By adding context, systems can make smarter decisions.
Example Context:
Let’s say you’re searching for books. The context might include:
- The user’s language preference (e.g., English)
- The current page of results (e.g., page 2)
- Filters applied (e.g., only books published after 2010)
In MCP, you might represent this context like so:
{
"language": "en",
"page": 2,
"filters": {
"published_year": { "$gt": 2010 }
}
}By sharing context, systems can tailor their responses and behavior to what the user actually needs. To tie it all together, let’s look at the protocol.
What Does “Protocol” Mean in MCP?
The protocol is a set of rules and formats that systems use to exchange models and context. It defines how information is packaged, sent, and interpreted. This is what enables seamless communication between different tools and services.
Example Protocol:
Imagine a client wants to fetch books from a server. Using MCP, the request might look like this:
{
"model": "Book",
"context": {
"language": "en",
"filters": { "author": "Ada Lovelace" }
},
"action": "list"
}The server responds with a list of books matching the context, using the shared model definition. Both sides know exactly what to expect, making integration smoother and less error-prone. With these basics in mind, let’s explore why MCP matters for developers.
Why Developers Should Care About MCP (and How to Build for It)
MCP is more than a technical standard—it’s a new way for software products to communicate and collaborate. If you build APIs, integrate with other products, or care about how users interact with your software, MCP is a concept you can’t afford to ignore. Understanding its impact can help you build more robust and future-proof systems.
How MCP Changes Software Collaboration
MCP enables products to work together in ways that weren’t possible before:
- Dynamic integrations: Products can adapt to new use cases without hardcoding every scenario.
- Personalized experiences: Context-aware APIs can tailor responses to each user or situation.
- Easier automation: Bots and workflows can reason about actions and data, not just follow scripts.
These benefits open up new opportunities for developers to create smarter, more adaptable software. To make this more concrete, let’s look at some practical examples.
Practical Example: Unlocking New Integrations with MCP
Imagine you’re building a SaaS note-taking app. Before MCP, if a user chatting with ChatGPT wanted to reference notes from a meeting with a sales prospect, they had to copy and paste between apps—slow and error-prone.
With MCP, your app can securely share just the right notes with ChatGPT when a user asks to draft an email to a prospect. ChatGPT can pull in the meeting summary and action items directly, helping the user write a more relevant email—without leaving the chat or switching tools.
User value:
- Instantly access meeting notes in ChatGPT to write better emails or follow-ups.
- No more manual copy-paste or context switching.
Business value:
- Your app becomes more useful to users who rely on AI tools, boosting engagement.
- Easier integrations mean more reach and new use cases with less effort.
This is the kind of seamless experience MCP enables—where AI and SaaS products work together to deliver more value than either could alone. Next, let’s look at what you can do as a developer to prepare for this future.
What Developers Should Do Now
- Learn the basics of MCP: Understand models, context, and protocol.
- Experiment: Try building a simple MCP server or client.
- Follow the ecosystem: MCP is evolving—watch for new tools, libraries, and best practices.
- Think context-first: When designing APIs, consider not just what data you expose, but how and why it’s used.
By taking these steps, you’ll be ready to take advantage of MCP as it becomes more widely adopted. Let’s wrap up with a quick summary.
Conclusion
The Model Context Protocol is more than just a new buzzword—it’s a practical approach to making software smarter, more flexible, and easier to integrate. By clearly defining models, sharing context, and following a common protocol, MCP opens the door to a new generation of tools and experiences.
Key takeaways:
- MCP brings together models (what data means), context (how and why it’s used), and protocol (how it’s exchanged).
- Using MCP, systems can communicate more clearly and adapt to users’ needs.
- Real-world examples include API testing, documentation, and automation.
Curious to learn more? Stay tuned for future posts where we’ll dive deeper into how MCP works in practice and how you can start using it in your own projects.