Learn where Model Context Protocol fits in an AI product, from connecting tools and context to designing permissions and useful user workflows.
AI products often need access to information outside a conversation: a project document, a database result or a tool that performs a specific action. Model Context Protocol, usually called MCP, provides a standard way for compatible AI applications to connect with servers that expose those capabilities.
Begin with the user’s task
Before selecting a connector, describe the work in ordinary language. What information does the person need? Which action should the assistant be able to request? What result would let the person verify success?
A document search tool, for example, is useful only if the returned passages include enough source information for the user to check them. A task creation tool needs an owner, a destination and a way to report what was created. Connectivity alone does not define the experience.
Separate the model from execution
Anthropic’s tool-use documentation describes a flow in which Claude requests a tool call and the host application returns its result. For client tools, the application executes the operation. That separation gives the product a place to validate arguments, enforce permissions and request review when needed.
MCP can help standardize the connection to a server. The application still needs to decide which capabilities are appropriate for a particular user and task.
Design authorization and approval deliberately
MCP’s authorization specification concerns access to protected resources. Human approval for a particular action is a separate product decision. A valid connection does not automatically mean every available action should run without review.
Use narrow permissions, clear tool descriptions and visible results. Treat retrieved content as information to evaluate; it should not gain authority to change the user’s instructions merely because it came from a connected tool.
Our current product direction
At VTech Studio, MCP integrations and Claude-based reasoning are planned elements of our Agent Collaboration Workspace. The product is in development. We are exploring how connectors can support useful team handoffs while preserving clear boundaries around context and actions.
Further reading
Anthropic: tool use overview
MCP authorization specification
MCP security best practices
