AI Engineering
Learn LLMs, RAG, agents, secure tools, and production AI through practical insurance examples.
MCP architecture: host, client, and server
MCP is a protocol for connecting AI applications to external tools and context. The host is the application using the model; a client is its protocol connection to a server; a server exposes supported capabilities. The model normally proposes operations,…
MCP tools and tool discovery
A tool is a named executable capability with argument metadata and a schema. Discovery lets a client obtain the server's available tool descriptions. A tool description helps the model choose a capability; it is not proof that the server or tool is…
MCP resources and prompts
Resources expose readable context through identified locations, such as policy documents. Prompts expose reusable task templates and arguments. Tools perform operations; resources provide content; prompts help compose a task.
Authentication, authorization, and permissions
Authentication establishes who a client/user is; authorization determines what that identity may do. MCP connection authorization and downstream business authorization are separate concerns. A valid connection does not automatically permit every customer's…
MCP versus REST, function calling, and plugins
REST is an HTTP API design style for application services. Function calling is a model interaction mechanism for proposing structured operations. MCP standardizes integration discovery and invocation/context exchange; a plugin is a packaging/integration…
Conceptual MCP server: four business tools
This example defines server-side contracts and dispatch logic, not a particular MCP SDK's registration syntax. Attach this registry to the selected SDK's authenticated request handlers, implement capability discovery, and encode its documented result…
Difficulty is an editorial estimate. Completion means you chose to mark a question as understood.