Tari Ibaba, Author at Coding Beauty

5 powerful MCP servers to make the most of GPT-5

By Tari Ibaba / Last updated on August 24, 2025

GPT-5 is out now and AI agents are smarter than ever — but real power comes when you connect them to real-world tools.

That’s where the Model Context Protocol (MCP) comes in. It lets GPT-5 talk to external services like your databases and repos — not just to understand them, but to use them.

Whether you’re building your own agent or using GPT-5 through tools like Claude, Cursor, or Copilot, these 5 ready-to-use MCP servers instantly upgrade your AI’s capabilities.

1. Firebase MCP server

If you’re already using Firebase, this server lets GPT-5 interact with your project just like you would from the CLI. It’s perfect for app automation, debugging, and user management — all from natural language.

Key features

Instantly bootstrap Firebase projects and apps
Manage Auth: list users, set custom claims, enable/disable accounts
Query Firestore and validate security rules
Send push notifications via FCM
Supports Data Connect (GraphQL), Remote Config, and Crashlytics

Powerful use cases

GPT-5 can spin up a full Firebase app with Firestore, Auth, and hosting
Automatically summarize recent Auth activity and flag risky behavior
Simulate rule access and debug failed reads/writes
Analyze crash logs and propose fixes directly from Crashlytics data

Get Firebase MCP Server: LINK

2. GitHub MCP Server

This official GitHub server is built to give agents full visibility into your repos. It’s great for AI-assisted issue triage, PR generation, and CI/CD diagnostics.

Key features

Local or hosted (OAuth) mode
Granular control: enable only repos, issues, pull requests, etc.
Read-only toggle for safe use
Supports Dependabot, CodeQL, GitHub Actions workflows
Plays well with Claude, Cursor, and other tools

Powerful use cases

GPT-5 can scan issues across multiple repos and suggest the highest-impact fixes
Generate summaries of PR conversations and flag unresolved feedback
Automatically file issues for flaky tests or broken workflows
Navigate GitHub Actions runs to debug CI/CD failures

Get GitHub MCP Server: LINK

3. Notion MCP

This hosted server lets GPT-5 act on your Notion workspace — fetching, editing, creating, and organizing content across pages and databases.

Key features

One-click OAuth setup for ChatGPT, Claude, Cursor, etc.
Unified search across Notion, Slack, Google Drive, and Jira
Page and database read/write support
Supports Streamable HTTP or stdio (via mcp-remote)
Great for knowledge management and workflows

Powerful use cases

GPT-5 can summarize meeting notes, create task trackers, or plan product launches
Automatically organize messy pages into structured databases
Generate content drafts based on workspace context
Answer questions using data from across Notion, Slack, and Google Docs

Get Notion MCP: LINK

4. DevDb MCP

DevDb turns your local databases into something GPT-5 can explore and reason about — without needing manual SQL writing or schema diving.

Key features

MCP server built into DevDb VS Code extension — also works for Cursor and Windsurf
Auto-detects common frameworks like Laravel, Django, and Rails
Supports Postgres, MySQL, SQLite, and SQL Server
One-click JSON config for agent setup
GUI tools for table editing and inspection

Powerful use cases

GPT-5 can inspect schema and generate queries from natural language
Document relationships and suggest schema changes
Auto-generate database migrations or seed data
Explore foreign key chains and infer business logic

Get DevDb MCP Server: LINK

5. Sentry MCP

This server connects GPT-5 to real-time error and performance data from Sentry — and lets it go beyond monitoring into automated debugging and even code generation.

Key features

OAuth setup with hosted Streamable HTTP or SSE fallback
Explore issues, events, traces, and performance regressions
View project/org metadata and DSNs
Integrated Seer tool for root-cause analysis and autofix
Supports local self-hosted Sentry too

Powerful use cases

GPT-5 can analyze top crashes, trace them to root causes, and suggest fixes
Automatically file detailed bug reports linked to Sentry errors
Monitor app performance and alert when KPIs regress
Use Seer to run auto-diagnosis and push PRs

GPT-5 is out in the wild now and these MCP servers take its raw intelligence and plug it into real-world workflows.

From spinning up Firebase apps to analyzing crashes in Sentry or navigating your entire Notion workspace — this is the future of AI: not just being intelligent, but now making things happen at massive scale in the real world.

GPT-5 coding is wild

By Tari Ibaba / Last updated on August 10, 2025

Developers are absolutely loving the new GPT-5 (def not all tho, ha ha).

It’s elevating our software development capabilities to a whole new level.

Everything is getting so much more effortless now:

You’ll see how it built the website so easily from the extremely detailed prompt from start from finish:

On SWE-bench Verified, which tests real GitHub issues inside real repos, GPT-5 hits 74.9% — the highest score to date.

Some people seem to really hate GPT-5 tho…

“SO SLOW!”

“HORRIBLE!”:

Not too sure what slowness they’re talking about.

I was even thinking it was noticeably faster than prev models when I first tried it in ChatGPT. Maybe placebo?

On Aider Polyglot, which measures how well it edits code via diffs, it reaches 88%.

“BLOATED”.

“WASTES TOKENS”.

GPT-5 can chain tool calls, recover from errors, and follow contracts — so it can scaffold a service, run tests, fix failures, and explain what changed, all without collapsing mid-flow.

“CLUELESS”.

But for many others these higher benchmark scores aren’t just theoretical — it’s making real impact in real codebases from real developers.

“Significantly better”:

See how Jetbrains Junie assistant so easily used GPT-5 to make this:

“The best”

“Sonnet level”

It’s looking especially good for frontend development, especially designing beautiful UIs.

In OpenAI’s tests, devs preferred GPT-5 over o3 ~70% of the time for frontend tasks. You can hand it a one-line brief and get a polished React + Tailwind UI — complete with routing, state, and styling that looks like it came from a UI designer.

The massive token limits GPT-5 has ensure that your IDEs have more than enough context from your codebase to give the most accurate results.

With ~400K total token capacity (272K input, 128K reasoning/output), GPT-5 can take entire subsystems — schemas, services, handlers, tests — and make precise changes. Long-context recall is stronger — so it references the right code instead of guessing.

GPT-5 is more candid when it lacks context and less prone to fabricate results — critical if you’re letting it touch production code.

Like it could ask you to provide more information instead of making stuff up — or assuming you meant something else that it’s more familiar with (annoying).

gpt-5, gpt-5-mini, and gpt-5-nano all share the same coding features, with pricing scaled by power.

The sweet spot for most devs: use minimal reasoning for micro-edits and bump it up for heavy refactors or migrations.

GPT-5 makes coding assistance feel dependable.

It handles the boring 80% so you can focus on the valuable 20%, and it does it with context, precision, and a lot less hand-holding.

GPT-5 is absolutely insane

By Tari Ibaba / Last updated on August 8, 2025

Wow this is huge.

GPT-5 is finally here and it’s completely unbelievable.

Practically destroying every other model in several AI benchmarks.

This is a massive upgrade from the GPT-4x’s.

Grok 4 the model I was just talking about the other day saying it was the best…

GPT-5’s coding abilities are unreal.

GPT-5 absolutely dominates industry coding tests with benchmark scores of 74.9% on SWE-Bench Verified and 88% on Aider Polyglot.

Unbelievably cheap API for such massive intelligence improvements.

SWE-Bench Verified simulates real-world GitHub issues, and GPT-5’s first-attempt solve rate outperforms every competitor.

Two BILLION tokens per minute?!

Like what do you even say about that.

I mean of course with such a mind-bogglingly low cost it’s no wonder why every AI tool (and their mother) will jump on it.

All our favorite IDEs instantly added support for it without even thinking.

Windsurf — generous as always:

But stats only tell part of the story. The real magic is in how it feels to code with GPT-5.

Cursor — you can try it for free…

You don’t have to walk it through every little thing. You just tell it what you want — “build me a login system,” “refactor this into something clean,” “find the bug here” — and it does it. One go. No back and forth. No babying it.

On Aider Polyglot the model showed exceptional multilingual coding skills — it generated and debugged code in dozens of programming languages without missing a beat.

Copilot & VS Code — never to be left out…

GPT-5 feels less like a tool and more like a teammate who never gets tired, never forgets, and somehow knows everything.

JetBrains — their Junie assistant I was talking about the other time has been out for some time now.

Super impressive snake game generation:

Everybody is absolutely loving it.

And OpenAI didn’t just drop one version — they’ve also released GPT-5-mini and nano. These are smaller, faster versions that still give you much of the coding power, which is great if you’re working on a budget or just need something lightweight for quick jobs.

All of this adds up to something big. The way we write software is changing. More and more, your job as a developer isn’t to type every line, but to describe what you want — clearly, thoughtfully — and let the AI handle the heavy lifting. GPT-5 lets you move faster, take on bigger projects, and focus on the parts of programming that actually require creativity and judgment.

Bottom line? GPT-5 coding is nuts. It’s fast, smart, flexible, and it actually understands what you’re trying to do. Whether you’re a pro dev or just getting started, this model is going to change how you think about building software.

Forever.

Clean code is dead

By Tari Ibaba / Last updated on August 6, 2025

If you’re still obsessed with writing “clean code” in 2025 then you are living in the stone age.

The clean code era is over. AI is here.

Your precious descriptive variable names,

Your admirable small functions,

Your meticulous design patterns and tireless refactorings…

All these things are far far less important now in the age of AI.

I can’t even remember the last time I created a variable by myself.

Wrote a function from scratch by myself?

Even created a file by myself? 🤔 (super rare)

Nobody codes like that anymore (sorry).

AI is here and modern developers don’t code that way.

Lol, you people and your annoying AI hype. Vibe coding is useless and AI can never replace programmers in any way. Stop talking nonsense.

Ha ha, yes I know some of you are still scoffing with disdain at the recent uprising of vibe coding and coding agents.

You proudly refuse to use even the slightest bit of AI in your coding.

Even basic Copilot code completions from 2021 are a no-no for you.

Well hate to break it to you but the world is leaving people like this behind.

There’s no going back — AI-first development is fast becoming the gold standard.

What matters most now is not clean or clear code — what matters is clear intent, goals, and context for the AI agent.

Not descriptive variable names — but now descriptive well-written prompts.

No longer just using the DRY principle in your code — but now also in all your AI interactions by setting powerful system prompts and personalized style guides.

No longer just about using the most intuitive and powerful libraries and APIs — but now using the all most powerful and highly capable MCP Servers.

Coding in 2025 is no longer about typing — it’s about thinking.

Actually it’s always been — but now the power of your thoughts has exploded drastically.

A thought, a design, an idea that took several days and weeks to be typed into life now takes a few minutes of prompting.

AI has astronomically expanded the power of our minds to do far more than ever before at any point in human history.

Should we still be wasting so much time obsessing over low-level details like whether we named our variables with snake case or camel case?

It’s time to level up and achieve our true potential.

Comprehensive context provisions, sophisticated prompting techniques, elaborate intent definitions, hyper-personalized system prompts, high-powered MCP server integrations…

These are the crucial things you need to focus right now.

These are what will turn you into a god-mode developer.

This new AI tool from Google just destroyed web & UI designers

By Tari Ibaba / Last updated on August 5, 2025

Wow this is absolutely massive.

The new Stitch tool from Google may have just completely ruined the careers of millions of web & UI designers — and it’s only just get started.

Just check out these stunning designs:

This is an absolute game changer for anyone who’s ever dreamed of building an app but felt intimidated by the whole design thing.

It’s a huge huge deal.

Just imagine you have a classic app idea — photo sharing app, workout app, todo-list whatever…

❌ Before:

You either hire a designer or spend hours wrestling with design software trying to create a pixel perfect UI.

Or maybe you even just try to wing it and hope for the best, making crucial design decisions on the fly as you develop the app.

✅ Now:

Just tell Stitch whatever the hell you’re thinking.

Literally just describe your app in plain English.

“A blue-themed photo-sharing app”:

Look how Stitch let me easily the design — adding likes for every photo:

Or, if you’ve got a rough sketch on a napkin, snap a pic and upload it. Stitch takes your input, whatever it is, and then — BOOM — it generates a visual design for your app’s user interface. It’s like having a personal UI designer at your fingertips.

But it doesn’t stop there. This is where it gets really cool — especially for developers.

Stitch doesn’t just give you a pretty picture. It also spits out the actual HTML and CSS code that brings that design to life.

Suddenly your app concept isn’t just an idea — it’s a working prototype.

How amazing is that?

Stitch is pretty smart too. It can give you different versions of your design, so you can pick the one you like best. You can also tweak things – change the colors, switch up the fonts, adjust the layout. It’s incredibly flexible. And if you want to make changes, just chat with Stitch. Tell it what you want to adjust, and it’ll make it happen. It’s a conversation, not a command line.

Behind all this magic are Google’s powerful AI models, Gemini 2.5 Pro and Gemini 2.5 Flash. These are the brains making sense of your ideas and turning them into designs and code. The whole process is surprisingly fast.

Who is this for?

Everyone. If you’re a complete beginner with zero design or coding experience, Stitch is your new best friend. You can create professional-looking apps without breaking a sweat.

It’s a fantastic way to rapidly prototype ideas and get a head start on coding for seasoned developers.

Right now, Stitch is in public beta, available in 212 countries, though it only speaks English for now. And yes, you can use it for free, with a monthly limit on how many designs you can generate.

It’s a super-powered starting gun for your app development journey. It streamlines the early stages to get you from a raw idea to a tangible design and code much faster.

And if you still want more fine-grained control, you can always export your design to Figma.

So, if you’ve got an app idea bubbling in your mind, Google Stitch might just be the tool you’ve been waiting for to bring it to life.

The most powerful AI model in the world just got a coding CLI

By Tari Ibaba / Last updated on August 7, 2025

Wow this is HUGE.

This most intelligent AI model on the planet just got an incredible new coding CLI.

Grok — the genius model from xAI sitting comfortably in #1 of several notable AI benchmarks.

Massive boost in speed and power in your software development.

Carry out massive context-aware tasks on your codebase with simple English right from your CLI:

Refactor functions or files
Edit project code based on coding standards
Generate shell scripts or bash commands
Automate git operations
Integrate with any MCP server

What took an hour of manual coding and debugging before → Now: a few minutes.

Just describe whatever you want and it takes care of the rest.

grok-cli is open-source and growing FAST with dozens of contributions already.

Conversational

Launch Grok CLI with the grok command:

Opens an interactive session
Remembers previous prompts
Lets you refine requests naturally — like a real-life conversation.

Context-aware

Grok CLI reads your project files — it knows what it’s editing.

Ask it to:

Change the logic in a file
Rename functions
Split code into modules

It works from actual source context — no guesses or hallucinations.

Shell and bash

Ask something like “compress all images in the assets folder” or “create a backup of the .env file” — Grok CLI will generate and run the correct commands — like zip.

Built-in

Grok CLI includes smart tools for file editing, git management, and navigation.

These tools run automatically when your prompt matches what they handle — giving you a clean interface without memorizing commands.

Project-specific instructions

By placing a .grok/GROK.md file in your repo, you can customize how Grok CLI behaves.

For example, you can specify preferred frameworks, coding standards, or architectural constraints. This makes it ideal for team workflows and codebases with strict conventions.

Large project context support

Grok CLI supports large context windows. It can review and reason over entire projects or multiple files at once, making it suitable for complex refactors, architecture reviews, or onboarding support.

Installation and setup

To get started you need:

Node.js version 16 or higher
A Grok API key from x.ai

Installation is straightforward:

npm install -g @vibe-kit/grok-cli

Then run:

grok

You can also run one-off prompts with:

grok --prompt "What does this function do?"

Set API keys with:

GROK_API_KEY environment variable
.env file
CLI --apiKey flag
~/.grok/user-settings.json file

You can also configure the base URL and model via the same methods.

Workflow integration

Grok CLI is designed to work with your existing tools. It supports both interactive and headless modes.

Interactive mode: Launch with grok to enter a conversational session.
Headless mode: Use --prompt for scripting, CI pipelines, or automation.
Custom configuration: Use .grok/settings.json to define per-project behavior.

The CLI makes it easy to integrate AI into your day-to-day development without changing your habits or workflow.

Extend Grok CLI with MCP

One of Grok CLI’s most advanced features is support for the Model Context Protocol (MCP).

With MCP, you can connect Grok CLI to external services—like issue trackers, deployment tools, or custom APIs—and control them through the terminal.

Example:

grok mcp add linear --command "node" --args mcp-linear.js

Grok CLI will now be able to read issues from Linear, create tasks, or pull data—all through AI commands.

The built-in mcp command supports:

add: add a new server
list: view connected MCP servers
test: verify a server’s functionality
remove: disconnect a server

This turns Grok CLI from a code assistant into a full-fledged AI agent platform.

Grok CLI is more than just another AI chatbot—it’s a new kind of developer tool.

It brings powerful language models right into your command line — blending natural language prompts with deep integration into your codebase and workflow.

If you’re a developer who spends time in the terminal and wants to work faster, write better code, and automate tedious tasks using AI, Grok CLI is absolutely worth a try.

This new AI coding agent from Google is unbelievable

By Tari Ibaba / Last updated on August 1, 2025

Wow this is insane.

This new AI coding agent from Google is simply incredible. Google is getting dead serious about dev tooling. No more messing around.

Jules is a genius agent can understand your intent, plan out steps, and execute complex coding tasks without even trying.

A super-smart teammate who can tackle coding tasks on its own asynchronously to make software dev so much easier.

It works seamlessly in the background so you can focus on other important stuff.

Gemini 2.5 Pro

Jules is powered by Gemini 2.5 Pro, which is Google’s advanced AI model for complex tasks. This gives it serious brainpower for understanding code.

And you bet 2.5 Flash is on its way to give it even more insane speeds.

When you give Jules a task it clones your codebase into a secure virtual machine in the Google Cloud. This is like a private workspace where Jules can experiment safely without messing with your live code.

It then understands the full context of your project. This is crucial because it helps Jules make smart, relevant changes. It doesn’t just look at isolated bits of code; it sees the whole picture.

After it’s done, Jules shows you its plan, its reasoning for the changes, and a “diff” of what it changed. You get to review everything and approve it before it goes into your main project. It even creates pull requests for you on GitHub!

Jules is quite the multi-tasker. It can handle a variety of coding chores you might not enjoy doing yourself.

For example, it can write tests for your code, which is super important for quality. It can also build new features from scratch, helping you speed up development.

Bug fixing? Yeah Jules can do that too. It can even bump dependency versions, which can be a tedious and error-prone task.

One cool feature is its audio changelogs. Jules can give you spoken summaries of recent code changes, turning your project history into something you can simply listen to.

Google has made it clear that you’re always in charge. Jules doesn’t train on your private code, and your data stays isolated. You can review and modify Jules’s proposed plans at every step.

It works directly with GitHub, so it integrates seamlessly with your existing workflow. No need to learn a new platform or switch between different tools.

Jules is currently in public beta, and it’s free to use with some limits. This is a big step towards “agentic development,” where AI systems take on more responsibility in the software development process.

It might sound like Jules is coming for developer jobs, but that’s probably not the goal here — at least for now.

Jules is meant to be a powerful tool that frees up developers to focus on higher-level thinking, design, and more creative problem-solving. It’s about making you more productive and efficient.

So, if you’re a developer, now’s a great time to check out Jules. It could really change the way you work.

MCP is an absolute game changer but what is it??

By Tari Ibaba / Last updated on September 11, 2025

MCP MCP… what’s this annoying MCP thing I keep seeing everywhere? What does it even mean?

Just another annoying AI buzzword that will die out soon right?

If you think that then you are dead wrong. This is HUGE.

MCP is massive new invention that is going to change everything.

It’s a major milestone for LLMs and agents and the AI revolution in general.

Bla bla bla… what does it mean Tari?? Start talking or GTFO!

Okay okay I will now but you really need to understand just how much of a game changer this is.

So this is the part where I tell you that MCP is an acronym that means Model Context Protocol — but that wouldn’t be saying much and I’ll be boring you to sleep.

The best thing is to give you a fascinating and powerful real-world analogy that you will understand instantly without even trying.

Think of the brain. The human brain.

Your brain is incredibly powerful — far far more intelligent than all the other species (combined??). Not even close.

But have you ever realized that your brain is… USELESS?!

Duuuude just effin explain MCP for me, I didn’t ask for your insults

No listen I’m not calling you dumb or anything like that — what I mean is — your brain can’t DO anything on it’s own, as far as the external world is concerned.

The only way your brain actually does anything in the physical world is by being connected to the rest of your body.

You could be the greatest genius the universe has ever seen.

You could THINK of the most beautiful poem, the most persuasive argument, the funniest joke in history…

You could IMAGINE the next great novel, the blueprint for a world-changing invention, the cure cancer…

You may KNOW where you want to go — the perfect destination, the goal, the person to meet, the protest to join, the stage to walk onto…

But without your biological tools — your mouth, your eyes, your hands, your feet… without these things, you are as good as non-existent.

There will absolutely nothing you can DO. You are completely powerless as far as the outside world is concerned.

So are you getting it now? This is the problem we’ve had with LLMs.

Since 2022 they’ve wowed us with their insane creativity and coding and summarization ability and so much more.

But they couldn’t really DO anything.

All they did was provide us with information. Even when AI agents came along, all they could do was reason and think (“think”).

It was our brains that then used the information to manually make things happen in the world.

This is what MCP changes forever.

They can think and process information, and now also perform real world actions.

They can get crucial data from ANY external data source to do ANYTHING.

AI agents are now in absolute god mode.

With MCP Servers the possibilities are now literally endless.

MCP Server. That’s just the name for anything that provide tools to an AI agent.

The MCP Server provides the tools. MCP tells it HOW to provide the tools.

For example:

GitHub MCP Server: provides tools that let’s the AI agent search any GitHub repo.
WhatsApp MCP Server: provides tools that let you search WhatsApp chats.

You see the real game changer of MCP is NOT actually about what all these incredible MCP Servers let you do.

Before MCP it was already somewhat possible to make LLMs interact with external services. For example manipulate the prompt or fine-tuning the model to provide some sort of JSON response of tools to call.

This was what platforms like AutoGPT and BabyAGI tried to do. It’s also why OpenAI and Google added function calling support to their models.

The main problem with these different attempts is exactly that — they were different. Or private like for GPT and Gemini function calling.

There was no standard and open way to let anyone create an AI agent that could have external tools plugged into it. Or to create tools to plug into any AI agent.

But now MCP has changed all that.

Now anyone can create programs that provide tools to make AI agents more powerful — without knowing anything about the agents beforehand.

That’s why we’ve been calling MCP the USB-C of AI applications.

USB-C standardized how tons of devices that needs to send all sorts of data to each other communicate.

Now as a manufacturer you no longer need to worry about the specific devices your users have and could need to connect your product to.

Just make sure it comes with a USB-C port and you’re good.

They can connect it to all the other billions of devices in the world that connect to USB-C — to provide or receive power or any kind of data.

And not just existing devices but ALL future devices — as long as they also support it.

This is the same game-changing thing MCP lets us do.

No more need for prompt manipulation or model-specific function calling.

And anyone can create agentic apps to use these tools, without knowing anything about the tools beforehand.

As long as the AI agent creator and MCP Server maker abide by the protocol, they will work with each other.

So that why it is really major milestone for the AI revolution.

Anything you can write code to do — an AI agent can do now.

Search your files in the cloud, update databases, control smart switches…

It drastically makes your AI agents waaay way more powerful — making YOU more powerful.

Huge Claude 4 coding news for this IDE

By Tari Ibaba / Last updated on July 20, 2025

Wow this is some incredible news…

Claude 4 Sonnet is now available in Windsurf with no API key! (No more BYOK in Cascade).

You no longer have to pay additional costs for the amazing model.

And the coding has been absolutely insane 👇

For a while now people have been pointing out how amazing they find Claude 4 Sonnet, especially compared to Gemini 2.5 Pro and GPT-4.1. And this isn’t just hype – the difference is showing up in real-world workflows, especially in long context tasks, clean refactoring, and deep architectural suggestions.

And remember this is the junior sibling of Claude 4 Opus — that incredible model that literally did all the coding by itself in a massive project for a full hour and a half…

That was 90 actual minutes of total hands-free autonomous coding genius with zero bugs. Opus 4 planned, coded, edited, and completed an entire full-stack project, and Claude 4 Sonnet shares a massive chunk of that DNA. In fact, for a lot of development tasks, especially within a controlled and optimized coding environment like Windsurf, the gap between Sonnet and Opus is surprisingly small.

What makes this even more monumental is the fact that Windsurf had previously been locked out of native Claude 4 support.

When Claude 4 launched back in May, Anthropic explicitly restricted direct Windsurf access, most likely due to the intense competitive landscape and the recent strategic moves surrounding Windsurf — including rumors of OpenAI acquiring the company and Google’s subsequent licensing deal for Windsurf’s code-generation platform.

The workaround was BYOK — “bring your own key.” That meant if you wanted to use Sonnet or Opus in Windsurf, you had to sign up for the Claude API separately, manage your own usage, and copy-paste keys manually. It worked — but it broke the seamless, fluid experience Windsurf is known for. It was a turbulent journey for users and the platform alike.

That’s now over. As of July 17, Claude 4 Sonnet is directly integrated into Windsurf again. You open the app, click a dropdown, and Sonnet’s there — no more hacks, no more limits. This signifies a successful restoration of support and improved collaboration between Windsurf and Anthropic, much to the relief of the developer community. It’s clean, fast, and shockingly good.

In fact, this might just be the best Claude experience available anywhere right now. The way Sonnet integrates into Cascade — Windsurf’s multi-agent AI flow system — feels like watching the future unfold in real time. Cascade breaks your prompts into intelligent stages, keeps memory across actions, and even offers live suggestions while you type. Now, with the raw power of Sonnet 4 plugged into that, it feels like pair programming with an elite coder who has already thoroughly digested your entire codebase.

The 200K context window means it can see everything — not just your current file, but your whole project: imports, dependencies, comments, TODOs, legacy bugs. Sonnet reads all of it, understands it, and then acts on it with unparalleled precision. You can ask it to upgrade your framework, optimize a specific component, or redesign an entire backend architecture — and it doesn’t blink. It just does it.

Add to that multi-file refactoring, which is handled intelligently without you needing to manually stage files or explain how everything is connected. Just describe the goal, and Claude intelligently does the wiring, making complex changes feel effortless.

The code it writes doesn’t feel “AI-generated.” It feels like code written by someone experienced — it follows the tone and patterns of your project, names things sensibly, and almost never makes you stop and think, “Wait, what is this supposed to be?”

For Pro users, you get 250 calls/month, billed at 2× credits — but for the sheer quality and effectiveness of Sonnet, that’s a deal that quickly pays for itself. Claude’s output is so effective that it drastically cuts out a ton of trial and error, which ultimately saves more time (and more credits) than even faster models that often need constant babysitting and manual correction.

Windsurf’s focus on enterprise-grade security and compliance (SOC 2 Type 2, FedRAMP High, HIPAA) enhances its value even more to make it a powerful solution for organizations seeking both efficiency and peace of mind.

This is all part of a major new string of updates from Windsurf, solidifying its position at the cutting edge of AI-powered development. With Claude 4 Sonnet now fully native, there’s truly no friction. No switching tabs, no key juggling, no API rate worries. Just open your editor and build.

And we haven’t even seen what happens if Opus 4 gets native access next.

This isn’t just a good update — it’s a massive leap forward for developer productivity and the future of coding. If you’ve been sleeping on Claude and Windsurf, now’s the time to wake up and ship.

5 ways to generate a SaaS Idea that earns you $10K per month

By Tari Ibaba / Last updated on July 15, 2025

You don’t need a kajillion-dollar app.

You just need something that generates enough income for you to own all your time and do what you love and live freely.

For most people out there $10,000 monthly recurring revenue from a SaaS is gonna be a fantastic way to achieve this.

It can take serious dedication and effort but it’s a perfectly achievable goal.

You just the right idea that actually solves a problem for the right audience, and proper marketing.

Five proven strategies with real-world examples to help you uncover a profitable SaaS idea that has the potential to hit that $10K MRR mark:

1. Solve your own pain points (or those of your network)

Look inwards.

What frustrations do you encounter in your daily work or personal life? Are there repetitive tasks you wish could be automated?

This person built a simple SaaS tool to save a major problem they had as a marketer:

Is there a process in your daily life that’s unnecessarily complex?

How it works:

Personal Experience: Think about tools you use regularly. What are their shortcomings? What features are missing? Have you ever thought, “There has to be a better way to do this?” That “better way” could be your SaaS idea.
Professional Network: Talk to colleagues, friends, and contacts in different industries. Ask them about their biggest headaches and inefficiencies. Often, people outside of tech don’t realize their problems can be solved with software, creating a prime opportunity for you.

Why it leads to $10K MRR: If you experience a pain point, chances are others do too. Solving a problem you deeply understand gives you an inherent advantage in building a truly useful product and marketing it effectively. Niche down from your broad experience. For example, if you find popular analytics tools too complex, you can build niche web analytics tool for small businesses.

2. Deep dive into niche communities and forums

The internet is a goldmine of unmet needs and frustrations, especially within online communities. People are constantly discussing problems, asking for solutions, and venting about inadequate tools.

This solo software engineer got the crucial initial audience for their app just by posting on Reddit:

How it works:

Reddit, Facebook Groups, Industry Forums: Join subreddits, Facebook groups, and specialized forums related to specific industries or hobbies. Look for recurring questions, complaints, and discussions around “what software would help with X?” or “I’m tired of using Y for Z.”
Product Review Sites: Sites like G2 and Capterra offer insights into existing software solutions. Look at negative reviews and identify common pain points users experience with current offerings. This can reveal gaps in the market.

Why it leads to $10K MRR: These communities represent an audience with a shared, urgent problem. By observing their discussions, you can pinpoint specific pain points and tailor a solution directly to their needs. A micro-SaaS targeting a niche audience that genuinely needs your solution is often more successful than a broad tool trying to serve everyone.

3. Improve upon existing (but flawed) solutions

You don’t always need to invent something entirely new. Sometimes, the most profitable ideas come from taking an existing product and making it significantly better for a specific segment, or addressing its major flaws.

How it works:

Competitor Analysis: Identify successful SaaS products in various categories. Then, analyze their weaknesses. Are they too expensive? Too complex? Lacking a crucial feature? Do they serve a broad audience but miss the specific needs of a smaller, valuable niche?
“Niche Down” the Giants: Large SaaS companies often cater to a wide audience, which means they can’t perfectly serve every niche. You can build a more specialized, user-friendly, or cost-effective alternative for a particular segment. For example, instead of a general website builder, create one specifically for wedding photographers or local bakeries.

Why it leads to $10K MRR: Competition validates a market exists. By offering a superior experience or a more tailored solution to an existing demand, you can capture a portion of that market and quickly gain traction. Focus on solving one problem exceptionally well for a defined audience.

4. Leverage emerging technologies (especially AI)

Every now and then a major technology breakthrough happens that opens up a world of opportunity for new IT tools including apps and software.

It happened with the Internet, mobile and app store, and recently it’s been happening with AI.

Not only do you get to build AI-powered tools, you get use AI in your development and ship your MVP much faster.

How it works:

AI Integration: The rise of AI and machine learning presents immense opportunities. How can AI automate tedious tasks, provide predictive insights, or personalize experiences within a specific industry? Think about AI-powered content optimization tools, AI SEO generators, or AI for video creation.
No-Code/Low-Code Tools: The increasing accessibility of no-code and low-code platforms means you can build and test SaaS ideas much faster and with less technical expertise. This significantly lowers the barrier to entry and allows for rapid iteration.

Why it leads to $10K MRR: Early adoption of emerging technologies can give you a significant competitive advantage. If you can build a solution that leverages these advancements to provide unique value, you’ll be well-positioned to attract early adopters and grow quickly.

5. Look for manual workarounds and “frankenstein” solutions

When people are solving a problem using a combination of spreadsheets, manual processes, and disparate tools, it’s a strong indicator of an unmet need that software could address.

This is what drove the creation of tools like Notion and ClickUp

How it works:

Observe Inefficiencies: Pay attention to situations where businesses or individuals are using clunky, manual workarounds to accomplish a task. This could be anything from managing orders with paper slips to using multiple free tools to cobble together a “solution.”
Identify Integration Gaps: Are people manually transferring data between different software programs? Are they performing repetitive copy-pasting tasks? A SaaS that integrates these disparate workflows or automates data transfer can be incredibly valuable.

Why it leads to $10K MRR: These “Frankenstein” solutions highlight a painful problem for which people are already expending time, effort, or even money.

Your SaaS can offer a streamlined, efficient, and often more affordable alternative, providing clear ROI and a strong incentive for adoption.

Beyond the Idea: Validation is Key

Once you have an idea, the next crucial step is rigorous validation. Talk to at least 5-10 potential customers in your target niche. Ask them about their current workflow, their biggest challenges, and what they would pay for a solution.

Don’t just ask if they “like” your idea; ask if they would pay for it and how much. Pre-selling before you build can be a powerful way to validate demand and secure initial revenue.

By focusing on real problems, understanding your niche deeply, and validating your assumptions, you’ll significantly increase your chances of building a SaaS that not only serves its users but also generates a healthy $10,000 per month.