MCP for AI Engineers

The Model Context Protocol helps AI applications connect to external tools and context in a more standardized way. For engineers, the key idea is simple: models are more useful when they can safely discover and use relevant capabilities.

Why MCP Matters

Without a shared integration pattern, every AI app invents a new way to expose tools, files, tickets, database schemas, or documents. MCP creates a common shape for those capabilities.

Tools and Resources

Tools are actions the model can request. Resources are context the model can inspect.

Design Principles

• Keep tool inputs explicit and typed.
• Scope permissions to the user's actual authority.
• Return structured errors that help recovery.
• Log calls for debugging and audit.
• Avoid tools that do several unrelated jobs.

type McpTool = {
  name: string;
  description: string;
  inputSchema: Record<string, unknown>;
};

Production Considerations

MCP does not remove product responsibility. You still need authentication, authorization, rate limits, review flows, and tests around tool behavior.

Next Step

Take the MCP quiz, then design one narrow tool that would help an AI assistant in your own workflow.