Everyone's chasing the newest AI model right now.
Claude Opus 4.7 just dropped, GPT-5.4 is out this March, Gemini 3.1 Pro is here.
And honestly? Chase them all, try every one. That FOMO is valid, these models are genuinely getting better every month.
But here's the part nobody talks about:
Every time you open a new model, and switch platforms, the context gets confused.

We started building AI Context Flow to explore this problem.

Not as another AI tool , but more like a layer across tools.

Hey PH!

AI memory is personal by default. Your context, your preferences, your saved info, none of it is visible to anyone else.

Which is great for privacy. Terrible for collaboration.

My partner and I are avid travellers. I plan, he executes. Last year I sent him more AI chat links than memes trying to get us on the same page for trip planning. It was absurd.

The numbers tell the story:

3264 users

4.99 rating

5.3% paid conversion

Our vision has been the same from day one: one knowledge base that works across all your AI tools.
And to achieve that, we launched our MCP Server in February. It connected to Claude Desktop, Claude Code, LM Studio, and most major AI agents. As far as we were concerned, the MCP chapter was closed.
Then we launched on AppSumo.
Within days, users kept asking for one thing: " ?"
Then came the questions about headless agents. CI scripts. n8n workflows. Users had intricate setups. They wanted a memory store for their OpenClaw agents, which they could also plug into Claude, which they could also call from a workflow runner. One memory, three completely different environments.
That's when we realized our MCP Server had a problem: it only supported OAuth. *facepalm*
(Getting a bit technical here, bear with me)
OAuth assumes there's a user sitting at a UI who can click "sign in" in a browser window. That's fine for Claude Desktop. It falls apart the moment you're running a headless agent on a server, or chaining four tools together in an automated workflow. Nobody is there to click anything!
So the team got to work. A few days later, we shipped Personal Access Tokens (PATs) for the MCP Server.
And that's how we ended up being the that works in three places at once:
In your browser, as a sidebar
Inside your chat agents, as an extension or MCP server
In your programmatic workflows, as an MCP with PAT-based authentication
New setup guides for everything are at docs.plurality.network.
Maybe a weekend project: give your OpenClaw or n8n agents a memory. Make them less forgetful, more intelligent, and a lot more useful.
If you are already running such setups, we have a lifetime deal going on for AI Context Flow: https://appsumo.8odi.net/m4n0da

But first, what is MCP?
MCP Servers, often called the USB-C of AI systems, have had a meteoric rise in 2025.
And the reason is plain to see. Without MCP, the complexity of integrating AI with external systems rises quadratically (esp. with the proliferation of AI agents). With MCP, it only increases linearly.
Practically, what this means is that you can connect your AI agents with any external data/tool source that exposes its functionality as per the standards of MCP. Kind of like a REST API, if you are an oldie like me in tech.
:
The MCP Servers I have been using the most (will create separate posts for these in the coming days):
: I tell ChatGPT what I want, and then use the Canva MCP to create an editable image of my concept. The file gets automatically added to my Canva account and I fix any issues manually. We all know AI-generated images have weird problems (esp. with spellings etc.), so Nano Banana wasn't really useful for me. A lot of my posts have pictures created this way (ping me if you want me to put together a short tutorial on this).
: Same as above. I use it to create mind maps of my brainstorming sessions with AI, where I can (sort of) create decision trees of how we arrived at a certain point.
: I haven't done it yet. I'm scared for privacy reasons, but the urge is strong. I hate meeting management, and as a founder, mother, and IT professional, I have to maintain my schedule down to the minute if I want to balance the various areas of my life.
: I have a lot of my context in Plurality's Memory Studio. With the Plurality MCP, I don't have to use the AI Context Flow browser extension and can instead use the MCP server directly on Claude Desktop. This helps me in three ways:
  I can pull in my context on Claude Desktop, Claude Code, and even with Cowork
  I don't have to keep pressing the optimize button to pull in context (MCP is seamless. Just chat, and it will do the rest)
  The overall experience is muuuuccchhh better than the extension

This guide shows how to add Plurality (or any other MCP server) to your different agents.
Which MCP servers are you using the most? Let's exchange notes.

box . ' .
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______________________________ .
Imagine: You're deep into a technical doc. Three browser tabs open. A Wikipedia article on one, an API reference on another, a blog post explaining a workaround on the third.

You find exactly what you need.

We built AI Context Flow because we believe the future of AI is about making all your tools and knowledge work as one. Using one AI agent has been the past and multi-agent is the future.

And every time you switch, your context should come with you. This is for you if:

• Your AI agents lose context every time you switch between projects

• You are drowning in saved articles that never talk to your AI

• You re in a team where everyone uses different tools but nobody shares the same context

We are offering $59 for lifetime access available for a limited time. You were the first ones to discover us, so it s only fair that you get the first lifetime plans.

700,000 people have quit ChatGPT in the past few weeks. Political backlash, ethical concerns over ICE using GPT-4, and a drop in product quality are all driving a massive wave of switching.

Most are landing on Claude. Some on Gemini. Many on both.

But every single one hits the same wall: how do you move your context?

All the preferences, projects, and workflows built up over months or years stay locked inside the old platform. The new one has no idea who you are.

Hey PH

I want to be upfront about something before I share what we built.

We've been building AI Context Flow - inline context injection via a browser extension that takes your personal context into AI tools as you use them. It's been working well, but it always had a ceiling.

Inline injection can only go so far. There are corner cases where you need deeper context. And the extension is browser-only. What about desktop apps, CLI tools, local models, mobile?
You shouldn't have to keep re-explaining yourself to every AI in every environment.

: '

Ever asked ChatGPT about "the login system" and watched it confidently mix up three different projects?

That's memory bleed i.e. when your AI assistant can't separate your contexts. Your healthcare client's specs bleed into your fintech code.

Your Python project gets Node.js suggestions from yesterday's conversation. Your personal writing style contaminates professional emails.