标签：#tools

A visual productivity tool to visualize your brian-dump Discussion | Link

The AI to-do list that does itself Discussion | Link

An AI workforce customized to your business Discussion | Link

AI keyboard that rephrases, translates, and more in any app Discussion | Link

A video greeting + buttons where you ARE the testimonial Discussion | Link

Turn AI-app feedback into agent-ready patch context. Discussion | Link

Turn errors, DOM, + screenshots into an AI-ready Markdown Discussion | Link

The ultimate 1-click hunter for blocked macOS ports Discussion | Link

If you've been following the AI-assisted development space, you've heard about the Model Context Protocol (MCP). But let's be honest—most MCP server lists are either too abstract or filled with niche tools you'll never use. In 2026, the ecosystem has matured, and I've curated 10 MCP servers that deliver real, measurable improvements to your daily coding workflow. Each entry includes: What it does Why it's useful (with a concrete scenario) Example config (using the standard .mcp.json or claude_desktop_config.json ) Let's dive in. 1. GitHub MCP Server (by modelcontextprotocol) What it does: Full read/write access to GitHub repos—issues, PRs, code reviews, and releases. Why useful: Instead of switching between your IDE and GitHub, your AI assistant can create a PR, request a review, and merge after CI passes—all from a single prompt. Example config: { "mcpServers" : { "github" : { "command" : "npx" , "args" : [ "-y" , "@modelcontextprotocol/server-github" ], "env" : { "GITHUB_TOKEN" : "ghp_xxxxxxxxxxxxxxxxxxxx" } } } } Scenario: "Create a new branch, add a fix for issue #42, push, and open a draft PR with a description." 2. Filesystem MCP Server What it does: Read, write, search, and manipulate files and directories on your local machine. Why useful: Your AI can now scaffold an entire project structure, rename files in bulk, or refactor code across multiple files without manual intervention. Example config: { "mcpServers" : { "filesystem" : { "command" : "npx" , "args" : [ "-y" , "@modelcontextprotocol/server-filesystem" ], "env" : { "ALLOWED_DIRS" : "/home/user/projects" } } } } Scenario: "Create a Next.js project with this folder structure, add a components folder, and move all page files into a pages directory." 3. PostgreSQL MCP Server What it does: Connect to PostgreSQL databases, run queries, and return results. Why useful: Debugging SQL queries or exploring a production database becomes a conversation. You can ask "Show me the last 10 orders with user details" a

Turn a prompt into a real HTML deck Discussion | Link

Every low-code vendor says "we support customization." But supports is a weasel word — recoloring a button is customization, and rewriting a scheduling engine is also customization. What actually decides whether a platform locks you in is how far up its extensibility goes. Here's a ruler. The three levels of customization Level What you can do Most no-code A real dev framework L1 — Config Fields, forms, workflows, permissions, themes ✅ ✅ L2 — Extension Custom components, custom actions, external API calls, business rules ⚠️ limited ✅ L3 — Framework Modify/extend the core, custom engines, deep rewrites, source under control ❌ wall ✅ (when open/controllable) Where it stops is where your ceiling is. Plenty of no-code platforms are delightful at L1, then hit "can't do that" at L2/L3 — and you retreat to writing your own thing next to it. Now low-code is the burden. Why you get locked in Black-box SaaS — no source, so any extension point the vendor didn't expose is simply out of reach. Two sources of truth — your extension code and the platform's config live in different systems, so a platform upgrade breaks/voids your work. Crippled self-hosting — the on-prem edition quietly drops extension capabilities. Closed ecosystem — only their component marketplace; your stack can't get in. How model-driven + open source raises the ceiling One unified extension system — your extensions (custom fields/components/actions) and the platform itself are built on the same metadata. Extension isn't a bolt-on, it's a first-class citizen — upgrades don't wipe your customizations. Source under your control — open + self-hostable is what makes L3 framework-level extension actually possible: an extension point you can't reach, you can add. AI at the metadata layer — AI-generated extensions land in the same model, so they stay maintainable and evolvable. That's the road Oinone takes: 100% metadata-driven, front + back end open source, self-hostable — customization reaches L3. How to stress-tes

Snap one photo, get listing-ready shots from every angle Discussion | Link

Local-first agent trust console with a safe local workspace Discussion | Link

Microsoft today released software updates to plug nearly 200 security holes across its Windows operating systems and supported software, a record number of fixes for the company's monthly Patch Tuesday cycle. Nearly three dozen of those bugs earned Microsoft's most dire "critical" rating, and exploit code for at least three of the weaknesses is now publicly available.

Automate physical work with a powerful robot Discussion | Link

Learn words in context with AI Discussion | Link

Latest audio model for live speech-to-speech translation Discussion | Link

One command to audit and fix your Mac's security Discussion | Link

Build always-on AI agents without managing servers Discussion | Link

Direct cinematic videos through chat Discussion | Link