What if your AI assistant truly understood your business?
What if your AI assistant didn’t just give smart answers, but truly understood your business, your data, your processes, and the way your organization works? What if the AI you already use every day could provide insights that are meaningful, relevant, and tailored to your reality?
Today, AI assistants like Claude and ChatGPT are becoming essential companions in the workplace. They help us think faster, write better, and explore ideas with ease. But despite their power, they still live outside the systems that matter most to your organization.
They rely on general knowledge and whatever information you paste into the chat. That means answers are often incomplete, irrelevant, hallucinatory or disconnected from your actual work. The result? You make strategic decisions based on faulty information.
Imagine the difference if your AI had context. If it could interpret questions knowing your company, your workflows, and your business data. Suddenly, AI answers aren’t just intelligent, they are informed, meaningful, and relevant to your day-to-day decisions.
Most AI tools respond based on general knowledge and whatever you manually provide. That means copying data from dashboards, pasting reports into prompts, and explaining context again and again.
For business users, this is inefficient and fragile. The moment data changes, the answer is outdated. AI can suggest what to do next, but it cannot fully understand your reality, and often, that’s the insight you really need.
Context changes everything. If your AI could see live business data, understand workflows, and learn how your organization operates, it could provide answers grounded in reality, answers you could trust and act on confidently. That’s where MCP servers come in.
Model Context Protocol, or MCP, is the bridge that makes this possible. MCP connects AI clients like Claude or ChatGPT to custom systems, such as your Betty Blocks applications, allowing AI to access your business context.
With MCP, AI can:
MCP transforms AI from a generic assistant into a context-aware partner. The AI stops guessing and starts understanding. For business users, this is a game changer, conversations in AI chat tools are no longer abstract, they are informed by your world.
Until now, MCP has mostly been discussed in developer circles, framed as a technical challenge. But its true power is for business users.
Business people already spend time in AI chat tools, they ask questions, explore scenarios, and make decisions. MCP makes these conversations meaningful by grounding them in trusted business data.
Low code platforms like Betty Blocks make this vision achievable. They empower business builders to create applications that mirror their data and workflows, without writing complex code. When these applications connect to AI through MCP, the AI gains the context it needs to provide insights that are truly relevant.
This isn’t about replacing developers. It’s about putting the people who understand the business best in control of what AI knows and how it supports their work.
Today, MCP is mainly used by developers because connecting AI to custom systems usually means writing code. You need to define APIs, manage data structures, and maintain integrations. That makes MCP powerful, but also complex. This is where low code changes the dynamic.
Low code platforms like Betty Blocks remove much of that technical complexity. Instead of building integrations from scratch, business users can visually model their data and workflows, in a way that already reflects how the business works. When these applications are connected to AI through MCP, the AI can use that existing structure as context. No custom backend development is needed to explain the business to the AI, because the application already does that.
With a low-code platform, tech savvy business users can:
In short, low code shifts MCP from a developer-only capability to a business-driven one. It makes context-aware AI accessible to the people who understand the business best.
The future of AI is not about replacing systems, it’s about making them easier to use. AI should be a natural interface on top of your existing applications, providing insights grounded in your business reality.
MCP fits that vision perfectly, bridging the gap between AI conversations and real business logic. By combining context-aware AI with low code, we can empower business teams to unlock smarter insights, make faster decisions, and explore opportunities they couldn’t see before.
Imagine what you could do if your AI knew your business as well as you do. That’s the future we are exploring, and we want to hear from you. How would context-aware AI change the way you work?