Hey everyone, we're now in the final week of the AppSumo campaign, so I wanted to check back in here and open things up.
I've been getting a lot of the same questions in DMs and comments, so let me address the most common ones:
"How hard is the MCP setup?" It takes less than 5 minutes. Full setup guide here: https://docs.plurality.network/t...
"Which tier should I get?" $59 if you're a solo builder. $149 if you're a power user who lives in AI tools daily. $339 if you have a team and want shared context across everyone.
The last 4 months have been intense, launching, testing, getting #1 product of the day and #1 productivity tool of the week here, late night bug fixes, getting featured in FORBES, & feature requests from hundreds of YOU! But watching this community grow has made every late night worth it.
Seeing this for the first time? Here's what AI Context Flow does:
It's a Chrome extension that creates one unified memory across all major AI platforms i.e. ChatGPT, Claude, Grok, Gemini, and Perplexity.
If I could sum up building in public in two words, it would be: course correction.
We launched AI Context Flow on Appsumo a few weeks ago, and turns out, managing AI context across tools is more nuanced than we thought. Thousands of people tried our product and one piece of feedback kept recurring: users needed more control over memory curation.
The demand was clear, but our product had missing features. So we did what any startup team does: we course corrected and went to our cave to build out what users needed.
Prompt Optimization was one of the first features we shipped in AI Context Flow.
We've grown a lot since then, evolving into a universal memory hub, but a big chunk of our userbase originally came for prompt optimization, and still loves it as a core part of their workflow.
The feedback we kept hearing was consistent: "I like the fast, one-click optimization, but sometimes I need more control."
More control over how the prompt gets optimized. More control over how context gets pulled in.
Just think for a sec. You've told different chat agents your role, your tech stack, your client preferences, your project constraints - hundreds of times across hundreds of conversations.
But where does all that live?
Scattered across chat histories. Fragmented across different platforms. Sometimes contradictory, & mostly out of date.
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.
We believe we are the best MCP native memory system in the market today. Don't believe us? Come join us and hack the product with us live. We're hosting a webinar where we'll walk through everything you can do with AI Context Flow and answer every question you have. We might be just the thing you were looking for in your own workflow.
No slides. No fluff. Just a live demo and open Q&A.
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.
