Using MCP to Monetise your Data

If you're building software, or offering anything remotely API-driven, you should be paying close attention to MCP. The Model Context Protocol, recently open-sourced by Anthropic, is quietly becoming the standard way that AI agents interact with external data and tools.

It's often described as the USB-C of AI.

So what does that mean for you, as a company offering data insights as part of a digital product (or hoping to)?

It means your product, can now be accessed by AI systems in a standardised way. And, more importantly, it means you can start to monetise those interactions in ways that simply wasn’t possible before.

AI is Becoming Agentic

Today’s most capable AI models & frameworks are agentic. They perform actions, make decisions, and string together workflows across systems. This solidifies this decades flavour of AI (LLMs) as, fundamentally, a workflow optimisation tool. But to be effective in workflow optimisation, they need access to data, APIs, documents, CRMs, databases, ticketing tools - you name it.

That’s where MCP comes in. It creates a standard language for connecting AI to external services. Instead of building bespoke plugins or integrations per platform, product/service providers can now support MCP and instantly gain access to a growing ecosystem of AI Agents.

By doing this, your offering up your product as a tool to the growing space of AI.

From Plugin to AI-Native

So here’s the opportunity: by wrapping your product in MCP, you’re not just integrating with AI - you're becoming AI-Native.

Say you run a sales intelligence platform. Instead of customers logging in and clicking around, they can ask an AI assistant, "Who should I follow up with this week?" That assistant pings your MCP endpoint, runs a query, returns results. It just became a new kind of API call - and one you can meter, track, and bill for.

That’s what companies like Zapier, Codeium, and Sourcegraph are already doing. They’re monetising AI-driven usage: premium features, usage-based billing, enterprise integrations - all integrated by MCP under the hood.

And it’s not just about revenue; it’s about relevance. As AI interfaces become the default way users interact with software, you want your product to show up in those workflows. Otherwise, you risk getting left behind.

What You Can Do Right Now

First, figure out what part of your product would be useful to an AI agent. That could be customer data, internal tools, document search, analytics, scheduling, or something industry-specific. Because we're (still) talking about LLMs here, you need to think in terms of semantics;

"How can I represent my unique product data, in a semantic way"

E.g. via SQL.

Next, build a stategy to monetisation. Or, at the least, internal optimisation. How can you now use MCP integration to boost revenue? Either through enhancing existing products/services, or by reducing latency to retreiving information within your business.

Then, once you have buy-in from your business build the MCP server. Anthropic provides open-source templates and SDKs in Python, TypeScript, and more. You don’t need to reinvent the wheel. If you already offer an API, this is an incremental lift.

If you don't have an API, this is your opportunity to build one - not just for human users, but for AI users too.

Finally, start charging for it. Maybe it's a new AI-powered feature tier. Maybe it's a per-use billing model for MCP tool invocations. Or maybe it’s bundled into your enterprise license as a differentiator. The key is, MCP gives you a hook into the next generation of interfaces, and a way to capture value from it.

The Bottom Line

MCP isn’t a gimmic - it's a tangible protocol. It’s becoming the default way AI systems interact with the world. And the companies who plug into that ecosystem early are going to be the ones that AI relies on tomorrow.

Your data. Your features. Your product. All usable by AI - if you let them be.

So ask yourself: what’s your AI access strategy? If you don’t have one, MCP might just be the easiest way to start.

Now go build something agents will want to talk to, and start turning that data into cash ££.