MCP, short for Model Context Protocol, is an open standard that lets AI assistants interact with external applications in a structured way. In practical terms, it gives tools like ChatGPT or Claude a consistent method for discovering actions, reading data, and performing tasks inside a business app.
For business teams, the reason this matters is simple: MCP turns an app from something an AI can only talk about into something an AI can actually use.
Why is MCP important now?
Anthropic introduced MCP on 25 November 2024 as an open standard for connecting AI assistants to systems where data lives, including business tools and development environments. OpenAI's current Apps SDK guidance also describes MCP as the open standard for connecting ChatGPT to external tools and data. Buzzy added MCP support on 14 January 2026, including OAuth 2.1 authentication and auto-generated CRUD tools from an app's data model. In other words, MCP is becoming part of the practical integration layer for AI assistants.
What problem does MCP solve?
Before MCP, every AI-to-app connection tended to become a custom integration. That meant separate work for authentication, tool definitions, data access, and action handling. MCP standardizes those patterns so AI clients and applications can speak the same language.
What does MCP expose inside an app?
MCP usually exposes three things:
Tools: actions the AI can perform, such as listing records, creating entries, or updating data
Resources: read-only context the AI can use to understand the app and its data
Authentication: a secure way to ensure the AI only accesses what the current user is allowed to access
Why is MCP useful for business apps specifically?
Business apps are full of structured records, workflows, permissions, and repeatable actions. That makes them a strong fit for MCP. An assistant can look up data, summarize status, create a request, or help a user complete a task, all without the app team having to build a separate AI product from scratch.
How does Buzzy fit?
Buzzy's MCP documentation is useful here because it describes a no-code path: the platform can generate MCP tools directly from the app's data model. In that model, teams define datatables, fields, and app behavior visually, and Buzzy generates the MCP surface that ChatGPT, Claude, or another MCP-aware assistant can use.
That matters because it lowers the cost of making a business app AI-usable. Instead of building a custom bridge for every application, the bridge is part of the platform.
What should teams watch out for?
MCP does not remove the need for good app design. If the data model is messy or access rules are unclear, the AI layer will inherit that confusion. The protocol helps with structured access, but the underlying application still needs to be well designed.
FAQ
Is MCP only for developers?
No. Developers may implement it directly in some environments, but platforms like Buzzy can expose MCP from a no-code app model.
Can MCP work with more than one AI assistant?
Yes. That is one of the main advantages of using an open standard rather than a one-off proprietary integration.
Does MCP mean the AI can do anything in the app?
No. The available actions still depend on the tools exposed by the app and the permissions granted to the current user.