Focused on sharing practical tech content about TypeScript, Vue 3, front-end architecture, and source code analysis.
The article introduces shadcn‑ui‑mcp‑server, a Node.js tool that implements a Model Context Protocol to let AI assistants read shadcn/ui component documentation, source code, and demos, enabling richer code suggestions and full‑page layout generation within editors like VS Code, Continue, and Cursor.
This tutorial walks through creating a eye‑catching like‑button effect using only CSS and a bit of JavaScript, covering parabolic particle motion, an optional oblique bounce, batch generation of random emojis, a +1 number animation, and a brief note on canvas alternatives.
The article examines why traditional try/catch becomes cumbersome in asynchronous JavaScript, then presents three cleaner solutions—a Stage‑1 try‑operator proposal, a custom safeAwait helper, and the community library await‑to‑js—detailing their syntax, benefits, drawbacks, and suitable use cases.
This article explains why the Model Context Protocol (MCP) is needed for LLMs, describes its client‑server architecture, data and transport layers, and provides step‑by‑step Python examples for creating both an MCP server and a client using FastMCP and low‑level APIs.
The article explains how breaking complex LLM tasks into sequential steps—known as prompt chaining—improves answer accuracy, debuggability, flexibility, and enables sophisticated AI workflows such as report generation, chatbots, and content creation using tools like n8n and Ollama.
Version 6.0 of the open‑source ECharts library introduces a sweeping visual redesign, dynamic theme switching, intelligent scatter jitter, new chord diagrams, axis breakpoints, matrix coordinate systems, label overflow protection, upgraded mark layers, and stronger custom series, making both new and existing projects more powerful and easier to develop.
The article explains how CSS has finally added native Masonry layout support, detailing its history, the two syntax options (display: masonry and grid-template-columns: masonry), performance benefits, practical code examples, and current browser support status.
This article provides a comprehensive, hands‑on tutorial for installing Ollama, Docker, and the open‑source Coze Studio on a local machine, configuring various LLM services such as Qwen 3, DeepSeek‑V3, and OpenRouter, and running the platform via Docker Compose to create and test AI agents.
The article traces the evolution of front‑end linting and formatting tools—from JSLint to ESLint, Prettier, and Rust‑based Biome—then introduces Ultracite, a zero‑config, Rust‑fast, AI‑friendly assistant that consolidates linting, formatting, Git hooks and AI integration into a single command.
The article reverse‑engineers Cursor’s Agent mode, explains its system prompt, enumerates the 16 built‑in tools, draws insights about the importance of model choice and tool usage, and outlines the components needed to build a similar open‑source coding assistant.
