Development

Tool use lets Claude call functions you define in your API request. MCP goes further — it lets Claude connect to external servers that provide tools, data, and prompts. MCP is the bridge between Claude and the rest of your infrastructure. This is Article 13 in the Claude AI — From Zero to Power User series. You should have completed Article 8: Tool Use before this article. By the end of this article, you will understand MCP architecture, use pre-built MCP servers, and build your own MCP server in both Python and TypeScript. ...

Claude can see. Send it a screenshot, a photo of a document, a chart, or a technical diagram — and it will analyze what it sees. Vision turns Claude into a powerful tool for data extraction, UI review, and document processing. This is Article 9 in the Claude AI — From Zero to Power User series. You should have completed Article 7: Messages API before this article. By the end of this article, you will know how to send images to Claude, extract data from documents, analyze screenshots, and optimize image costs. ...

These ten concepts appear in almost every Python project. If you know all of them, you can read and write real Python code. If you are missing one, that is the one that trips you up on every project. 1. Variables and Data Types Python infers types automatically. No declaration needed. name: str = "Alex" age: int = 25 score: float = 9.5 active: bool = True nothing = None print(type(name)) # <class 'str'> The four built-in collection types: numbers = [1, 2, 3] # list — ordered, mutable point = (10, 20) # tuple — ordered, immutable tags = {"python", "dev"} # set — unique items user = {"name": "Alex", "age": 25} # dict — key/value pairs Use type() to check the type of any variable at runtime. Use type hints for documentation and IDE support. ...

Claude is smart, but it cannot check the weather, query your database, or call your APIs. Tool use changes that. You define functions, and Claude decides when to call them. This is Article 8 in the Claude AI — From Zero to Power User series. You should have completed Article 7: Messages API before this article. By the end of this article, you will know how to define tools, handle the tool use flow, force tool execution, and build a working multi-tool assistant. ...

In the previous tutorial, you built a complete microservice with REST. Now let’s learn gRPC — a faster alternative for service-to-service communication. gRPC is a high-performance RPC framework created by Google. It uses Protocol Buffers (protobuf) for serialization and HTTP/2 for transport. It is faster than REST+JSON, supports streaming, and generates client and server code automatically. When to Use gRPC vs REST Feature REST gRPC Format JSON (text) Protobuf (binary) Speed Good Faster (2-10x) Streaming Limited (WebSocket) Built-in Browser support Native Needs proxy Code generation Optional (OpenAPI) Built-in Human readable Yes No (binary) Use REST when: ...

In the previous tutorial, you learned Docker for Go. Now let’s put everything together and build a complete microservice. This is a project tutorial. You will build a notes API from scratch using the skills from the entire series: Gin for routing, PostgreSQL with sqlx for storage, JWT for authentication, validation for input, slog for logging, and Docker for deployment. What We Are Building A notes microservice with these endpoints: Method Path Description Auth POST /api/register Create account No POST /api/login Get JWT token No GET /api/notes List user’s notes Yes POST /api/notes Create a note Yes GET /api/notes/:id Get a note Yes PUT /api/notes/:id Update a note Yes DELETE /api/notes/:id Delete a note Yes GET /health Health check No Project Structure notes-api/ cmd/ server/ main.go # Entry point internal/ handler/ auth.go # Auth handlers (register, login) notes.go # Note CRUD handlers middleware.go # JWT middleware model/ user.go # User struct note.go # Note struct repository/ user.go # User database operations note.go # Note database operations service/ auth.go # Auth business logic go.mod go.sum Dockerfile docker-compose.yml This follows the clean architecture from Go Tutorial #10. ...

In the previous tutorial, you built a CLI tool with Cobra. Now let’s package your Go applications with Docker. Go and Docker are a perfect combination. Go compiles to a single static binary. No runtime, no dependencies, no virtual machine. You can run a Go binary in a Docker image that contains nothing else. The result? Production images under 15MB. A Simple Dockerfile Start with a basic Dockerfile for a Go web server: ...

In the previous tutorial, you learned about generics. Now let’s build something practical — a command-line tool. Go is one of the best languages for building CLI tools. It compiles to a single binary with no dependencies. Tools like Docker, kubectl, Hugo, and GitHub CLI are all written in Go using Cobra. In this tutorial, you will build a complete TODO CLI app. What is Cobra? Cobra is a library for creating CLI applications in Go. It provides: ...

The Messages API is the foundation of everything you build with Claude. Every feature — tool use, vision, streaming, caching — goes through this API. Understanding it deeply will make every other article in this series easier. This is Article 7 in the Claude AI — From Zero to Power User series. You should have completed Article 2: Getting Started before this article. By the end of this article, you will know how to build multi-turn conversations, stream responses in real time, and track your token usage. ...

In the previous tutorial, you learned API best practices. Now let’s explore one of Go’s most powerful features — generics. Before Go 1.18, you had two choices for writing reusable code: use interface{} (losing type safety) or write the same function for every type. Generics solve this problem. You write a function once, and it works with any type that meets your constraints. The Problem Without Generics Imagine you need a function to find the minimum value in a slice. Without generics, you write one function per type: ...