تحديد نطاق المشروع والأدوات

You have learned the pieces; now you build a complete server. This capstone wraps one real service into a tidy, installable MCP server. 🚀

Before any code, name the job your server helps with. A clear goal like search my notes keeps every later decision focused and small.

Choose a single concrete backend: a notes folder, a SQLite database, or one public API. One source keeps the capstone shippable, not sprawling.

Write down what the AI should be able to do, like search, read, and add. This short capability list becomes your map of tools and resources.

Split your list: things that change state are tools, things that only fetch context are resources. This sorting decides each primitive up front.

For each tool, jot a name, its arguments, and what it returns. A quick signature sketch catches missing inputs long before you write logic.

Pick one piece of read-only context to expose as a resource, such as a single note by its id. Resources feed the model without taking action.

Add one reusable prompt the user can trigger, like summarize this note. Prompts package your best instructions so callers do not retype them.

Decide what finished looks like now: the server loads, lists three tools, and answers one real query. A clear scope stops endless feature creep.

Give your project a short, descriptive name like notes-mcp. Clients show this name to users, so make it instantly tell people what it does.

Capture the plan in one short spec file: goal, backend, tools, resource, and prompt. This page becomes your checklist as you build the rest.

Let us confirm how you sort capabilities.

You scoped a real project: one goal, one backend, and a tight list of tools, a resource, and a prompt. A clear plan makes the build easy. 🎯