Codesamplez.com - Programming & Development Tutorials

WebMCP Fundamentals: A Hands-On Guide to Building Agent-Ready Web Pages

Rana Ahsan — Wed, 21 Oct 2026 14:21:00 +0000

AI agents waste effort guessing which buttons to click. WebMCP lets your page hand them a proper menu of tools instead. In this hands-on guide, you'll build a small task tracker, register three agent-callable tools, test them in Chrome DevTools, and connect a real agent, all with plain JavaScript.

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Server Side Request Forgery (SSRF) Explained for Developers

Rana Ahsan — Mon, 03 Aug 2026 19:14:31 +0000

Server Side Request Forgery (SSRF) tricks your own server into fetching malicious URLs — leaking cloud credentials, exposing internal services, and bypassing firewalls entirely. This guide walks through a real vulnerable Python app, explains every attack vector including DNS rebinding, and builds a production-ready fix with six layers of defense.

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Git Worktree Explained: Work on Multiple Branches at Once

Rana Ahsan — Wed, 06 May 2026 19:32:18 +0000

Git Worktree is Git's built-in superpower for checking out multiple branches into separate directories — simultaneously. No stashing, no duplicate clones. This tutorial walks you through the complete lifecycle: adding, using, troubleshooting, and removing worktrees, with real hotfix scenarios and pro tips you won't find in the official docs.

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JSON vs JSONC vs JSON5: The Complete Guide for Devs

Rana Ahsan — Wed, 15 Apr 2026 14:15:00 +0000

JSON, JSONC, and JSON5 look almost identical but break in completely different ways. This guide covers the real grammar constraints, parser compatibility traps, trailing-comma gotchas, and a decision framework to pick the right format for APIs, configs, and CI pipelines.

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SnapDrift: Free Auto Visual Regression Testing On GitHub Actions

Rana Ahsan — Fri, 20 Mar 2026 00:32:00 +0000

SnapDrift is a free, open-source visual regression testing tool built for GitHub Actions. It captures full-page screenshots on every push, compares them pixel-by-pixel against your baseline, and reports drift directly in your pull requests. No SaaS dashboards, no per-screenshot pricing — just two Actions and a JSON config.

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Local LLM for Coding: Free AI Coding Agent With Ollama + Claude

Rana Ahsan — Wed, 11 Mar 2026 18:33:32 +0000

This guide walks you through setting up a fully private, local LLM for coding on your own hardware. From model selection and hardware planning to IDE integration with Ollama and Continue.dev, you'll build an AI coding stack where no code ever leaves your machine.

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Best AI Coding Agents in 2026: The Complete Beginner’s Guide

Rana Ahsan — Wed, 18 Feb 2026 23:27:01 +0000

The best AI coding agents in 2026 don't just autocomplete your lines — they plan, execute, and debug entire features autonomously. Whether you're a weekend hacker or a seasoned engineer, this guide breaks down Google Antigravity, Claude Code, OpenAI Codex, OpenCode, and KiloCode so you can pick the right tool and ship faster.

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A step-by-step guide to building a simple RAG system in Python

Rana Ahsan — Thu, 05 Feb 2026 19:44:06 +0000

Build a small, practical Retrieval-Augmented Generation (RAG) system in Python: chunk your docs, embed them, store vectors in Chroma, retrieve top matches, and have an LLM answer using only that context. Includes a runnable example and common pitfalls.

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Add Memory to AI Agent: Python Tutorial for Beginners

Rana Ahsan — Thu, 22 Jan 2026 16:00:00 +0000

Discover how to add memory to AI agent systems using pure Python—no frameworks required. This hands-on tutorial walks you through building short-term conversation tracking and long-term persistent storage, transforming stateless chatbots into context-aware assistants that actually remember your conversations and preferences across sessions.

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Model Context Protocol For Beginners: Superpower of AI Agents

Rana Ahsan — Thu, 08 Jan 2026 22:19:59 +0000

Model Context Protocol (MCP) is Anthropic's open standard that lets AI agents securely access your tools, databases, and APIs. Think of it as USB-C for AI—one universal protocol connecting language models to everything they need to actually get work done in your environment.

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