Need your GoodBarber Custom Code to behave differently for a logged-in user — show premium content, greet a member by name, hide a section from anonymous visitors? Whether you wrote that code yourself or generated it with the AI Extension Builder, it asks the App API who's connected through gb.user.getCurrent(). But the back-office preview has no real login, so for Membership apps that call always lands in the error path. This guide explains how the current user behaves in the preview for every app type, and gives you a copy-paste way to test as a logged-in member. A lot of Custom Code needs to know who is using the app right now: showing premium content, greeting members by name, hiding a section from anonymous visitors, adapting a checkout. The GoodBarber App API gives you the current user through gb.user.getCurrent().And Custom Code isn't only something you write by hand anymore. With GoodBarber's AI Extension Builder, you describe the section you want in plain language and the assistant generates the extension for you — code that plugs straight into the same GoodBarber App API. Hand-written or AI-generated, it calls gb.user.getCurrent() the same way, and you test it the same way. So this guide applies whether you typed the code or prompted for it.But here's the catch every developer eventually hits: inside the back-office preview, there is no logged-in user. The preview is just a render of your app — there's no login screen, no session, nothing to authenticate against.For most app types, GoodBarber quietly works around this for you, so testing "as a logged-in user" just works. For the Membership extension, it doesn't — and that's on purpose. This article walks through how the current user behaves in the preview for each app type, and gives you a simple, copy-paste way to test the trickiest case: a logged-in member.

Gartner says 33% of enterprise software will include agentic AI by 2028. Your GoodBarber Skills already qualify — here's how to activate them, no code needed.

Agencies and resellers: run a daily review across every client app from one AI agent. How to manage multiple GoodBarber apps with AI through MCP — in 3 steps.

AI content publishing for editors and nonprofits: let an agent publish, schedule and run your app's content calendar through MCP — shown live, step by step.

Most app-builder comparisons pit two opposite philosophies against each other: a tool that makes you design a database against one that hands you finished features. GoodBarber and BuildFire are not that comparison. They agree on the method — you configure pre-built features instead of wiring atomic building blocks, and you reach a publishable app fast. That shared starting point is exactly why the decision between them is interesting: when two tools take the same shortcut, the question stops being "which approach" and becomes "what do you actually ship, and how well does it hold up?"To answer that concretely, we ran the same brief through both platforms: AURORA, the test app we use across this whole series.BuildFire is a mature, capable platform with thousands of live apps and a deep plugin catalog. The honest answer is that the two tools fit different operators — and the clearest fault lines run through native output, what's included in the subscription, and the economics of running apps over time.

Apple rejects 42% of apps on their first submission—and that’s just one of the hurdles after the demo. What vibe coding overlooks about building a mobile app.

The 2026 World Cup has kicked off, and the matches are about to grab everyone's attention — a chance to keep your audience close and bring in a new one, right inside your app. Here's how to add a a match schedule and results section to it — each match's score, the next match up front, kickoff time in the visitor's local zone — starting from a single prompt, with GoodBarber's AI Extension Builder. From June 11 to July 19, 2026, 48 teams and dozens of matches will set the rhythm for six weeks of worldwide attention. Meanwhile, your community is following the scores on five other apps. None of them carries your name.A fixtures and results section is exactly the kind of page that, until recently, called for a developer. Today, you describe it and it builds itself. Here's how.

For fifteen years, software raced to be easier for people to operate. That race is ending. The next one is whether your app can be operated by an AI agent at all. Here is what "agent-ready" means, the five things it takes, and why 2026 is the year it stops being optional. You run an app. Every week you open a dashboard, publish a few things, schedule a push, check yesterday's numbers, fix a price. That dashboard got friendlier every year — the whole no-code promise, and it worked. Millions of people now operate professional apps without code.But the operator is changing. People are starting to hand that weekly routine to an AI assistant: "Publish these three articles, schedule a push for each, and tell me which section lost readers last week." The assistant doesn't want a friendlier dashboard. It wants an interface it can call.That single fact reorders everything. The interface that wins the next decade isn't the one humans like best. It's the one an agent can drive.

GoodBarber's theme library has always given merchants a professional head start, and it keeps growing. The latest additions are a set of eCommerce-oriented themes, each designed like a real brand with its own distinct look, proof of just how much range a GoodBarber app can have. Whatever style your store calls for, the right theme takes you from idea to launch far faster than designing everything yourself. If you run an online store or a local business, you already know how your brand should come across. The vision isn't the hard part. The hard part is translating it into a polished app, screen after screen, when design isn't your job. Which colors belong together? How big should the headings be? How do you keep everything consistent from one screen to the next? For most merchants, that's where the project quietly stalls: not in building the app, but in designing it.Starting from nothing sounds like creative freedom. More often it's a roadblock. What moves a project forward is a credible starting point: something that already looks right, ready to be shaped around your brand and your catalog instead of assembled piece by piece.

You've got a GoodBarber app. You've seen our announcements about the "MCP server," AI, "agent-ready" apps — and assumed all of it was for developers. It isn't. In five minutes, from ChatGPT, you can run your app just by talking to it: update a price, publish an article, send a push. No terminal, no code. Here's how, with five copy-paste prompts to get you started. Let's settle it right away, because it's the misunderstanding that stops everyone: you don't need any technical skills. No terminal, nothing to install, not a single command line. If you can write a message, you can run your app.The "MCP" our other articles talk about is simply the secure bridge between ChatGPT and your app. You'll never have to touch it, or even remember what those three letters stand for. You plug it in once, and you forget it.What you use is ChatGPT: the OpenAI assistant you've probably already opened a hundred times. The same chat window. The only difference, once it's connected to your app, is that it now knows how to act on it.We've been building tools for non-technical creators since 2011. This one follows the same rule as the rest: more power, less complexity.

The action you want from your users deserves to be reachable at all times, whether they are reading an article, browsing a product page, or moving from one tab to another. The Floating Button gives it exactly that place: a button defined once, present wherever your users need it, with no need to place it again screen by screen.

The short answer: with MCP, the API explains itself to the machine — you don't build requests by hand.A classic REST integration means reading API docs, building each HTTP request, handling auth and pagination yourself. MCP (Model Context Protocol) inverts that work: your GoodBarber app exposes its operations as tools that any MCP client can discover and call. Our test app — a Content App — exposed 62 tools the moment we connected: articles, paragraphs, events, maps, galleries, videos, sounds.n8n matters here because it's one of the rare automation platforms with a native MCP Client node — and because its AI Agent nodes can hand those 62 tools to Claude and let the model decide which to call. Zapier-style platforms automate apps; n8n + MCP automates your app.REST + classic automationMCP + n8nIntegration workOne hand-built request per actionTools discovered automaticallyAuthAPI keys per requestOne OAuth connectionAI in the loopYou parse, AI sees fragmentsThe agent calls tools directly

Every app platform in 2026 calls itself AI-powered. Bubble wants you to build AI agents. Lovable generates an app from a prompt. GoodBarber does something different — and, for most businesses, more useful: it turns the app you already run into an AI backend, a live system any AI agent can operate on your behalf. No-code app builders approach AI agent integration in two ways: they help you build agents, or they make your existing app callable by them.The agent-builder modelThe AI backend modelWhat the AI doesGenerates or powers your app's logicCalls your app's operations on your behalfYour starting pointBuild — or rebuild — on their platformYour existing app is already the targetWhere complexity livesIn workflows and databases you maintainIn the agent; your app simply respondsExamplesBubble, Lovable, Base44GoodBarber, through MCPBubble's pitch is sincere and, for its audience, accurate: if you're assembling a custom software product, building AI agents on Bubble's database-and-workflow engine is genuinely powerful. The same goes for prompt-to-app tools when what you need is a prototype by tonight.But notice what both ask of you first: a build. A schema, workflows, screens — or at the very least a migration.For a merchant with an existing app and real customers, that's the wrong starting point. You don't need to rebuild anything. You need your app to respond to AI commands.

Protecting underage users is no longer optional. A growing number of laws now require apps to adapt their behavior to a user's age — and getting it wrong can mean removal from the stores. Age Protection builds that compliance straight into your native GoodBarber apps, with no code on your side. Here's how to turn it on, and what changes for your users. Over the past few years, several countries — starting with the United States — have tightened the rules around protecting minors on digital platforms. These laws require apps to account for a user's age when deciding which features they can access. Any app that collects data, serves ads, or enables social interaction now has to apply specific restrictions whenever the user is a minor (under 16).On a custom-built app, that's real work: age detection, conditional logic on every sensitive feature, and ongoing maintenance every time the law changes. With GoodBarber, age verification is built natively into your iOS and Android apps. You flip one switch; the rest follows.

GoodBarber's MCP server makes your app a first-class tool any AI agent can drive — with 44 open-source skills, native Claude Code and Cursor support, and an endpoint built for agencies. Three articles showed how GoodBarber's MCP server works for creators. This one is for the people building on top of it.If you're catching up, the server launched for the shop, then reached your content, then push notifications.

This month the spotlight is on the GoodBarber MCP Server — now live for both Shopping and Content apps — alongside a long list of fixes across the board.The GoodBarber MCP Server is live: connect your app to AI assistants and manage everyday tasks in one sentence.Smarter push notifications with AI: the MCP server now creates push notifications with scheduling, destinations, and precise targeting for platforms, groups, subscriptions, or specific users.Your CMS, now reachable by the MCP server: articles, events, maps, galleries, podcasts.

Thunkable comes with a pedigree most app builders can't claim: it was spun out of MIT App Inventor, the project that taught a generation how to assemble apps from visual blocks. Fifteen million apps later, that heritage shows — the drag-and-drop editor is genuinely approachable, and the recent AI Builder layer ("iOS and Android—built by chatting") lowers the barrier even further. When we sat down to build AURORA on it, getting a first screen running was fast and frankly fun.The question that AURORA forced us to ask wasn't "can I build the first version?" — it was "what exactly am I shipping to the App Store, and what happens when the app gets bigger?" Thunkable's own marketing says it produces real native apps. Community reviews describe a block-interpretation layer that slows down as logic grows. That gap — between the promise of native and the experience of running a real app at scale — is what this comparison is about.This is part of our ongoing series, where we run the same AURORA brief through each tool honestly. If you're also weighing Adalo, Glide, FlutterFlow, or Bubble, you'll find the same method applied to each.

AppSheet is a Google product, which means it arrives with a level of enterprise credibility that few competitors can match. It is embedded in Google Workspace, backed by Google Cloud infrastructure, and used by organizations like Airbus, Husqvarna, and Solvay. That is a genuinely strong signal. When we applied the AURORA brief to it, we quickly understood that AppSheet's credibility is real — it just applies to a different job than the one we were trying to do.AppSheet is built for internal business tools: an inventory app for your warehouse team, an inspection form for your field technicians, a CRM for your sales reps. AURORA is a consumer-facing mobile app — one that goes in the App Store under your brand, gets downloaded by customers you've never met, and needs to be operated daily by a marketing team who will never touch a spreadsheet. These are two different problems. The fact that both get called "no-code app building" is where the confusion starts.This is part of our ongoing series — the same AURORA brief, applied honestly to each tool we've evaluated. If you're also comparing Adalo, Glide, Bubble, or any other platform in the no-code space, you'll find the same framework across all of them.

Since its launch, the GoodBarber MCP server has opened up a new way to manage an app. Instead of navigating through every back-office menu, you can ask an AI assistant to perform certain actions for you, using natural language. Creating a push notification can seem simple at first: write a message, choose an audience, send it.But in real use, requests are often more precise:send the notification tomorrow morning;target only iOS and Android users;open a specific app section;redirect to an article, product, or URL;target a user group;send a message to a specific user;schedule the send according to each user's local time.Until now, this kind of setup required going through several settings manually. With the enriched MCP server, users can express their need in a natural sentence.For example:"Send a push notification Friday at 10 a.m. to iOS and PWA users to announce the release of my new show, and open the Web TV section when they tap it."The assistant then needs to understand three essential elements:the message to send;the audience concerned;the action to trigger on tap.This is exactly what makes the update useful: AI does not just write text. It interprets a complete communication intent.

Bolt.new arrived in October 2024 and immediately became impossible to ignore. We watched it reach $20 million in ARR in two months and decided we needed to build something real on it — not run a feature checklist, but actually go through the process of shipping an app from scratch. We used the same brief we've applied across this entire series: AURORA, a luxury travel guide app that needs native store distribution, daily content updates, push notification campaigns, user management, and a working e-commerce layer.We built it on Bolt.new. We built it on GoodBarber. What follows is what we found — including the parts where Bolt impressed us, and the parts where the experience diverged in ways that matter depending on what kind of app you're building and who will be running it.This is part of our ongoing series — the same brief, applied to every major tool we've evaluated. If you're also looking at Base44, Emergent, Adalo or FlutterFlow, you'll find a consistent frame across all of them.