AI Context Flow
Reusable AI Memory for Smarter Prompts Anywhere
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Are you a product builder or a messenger between different AIs?

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If you're building a product with AI tools, here's how your morning probably looks:

  • Open ChatGPT. Paste your project context. Ask your question. Get a decent answer.

  • Switch to Claude for something else. Paste your context again. Different tool, same briefing.

  • Hop into your codebase with Codex. Paste context again.

You're not just a builder anymore. You're a context delivery system.

The indie hackers I've talked to who use AI most effectively have one thing in common: they've figured out how to stop babysitting their tools and just use them.


That's the whole premise of AI Context Flow. Your project knowledge lives in one place. Every tool you use pulls from it automatically via MCP. The briefing happens once, not ten times a day.


If you're shipping solo or with a tiny team, this is the kind of leverage that actually moves the needle.

2-min overview:


Lifetime deal on AppSumo until June 20:


What does your current AI context workflow actually look like? Share your hacks below!

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Haha, very relatable 😅

For me it's mostly ChatGPT, Android Studio, browser tabs, and lots of copy-pasting context between them. Sometimes I spend more time explaining my project again than actually building the feature.

then you know which product to try out next 😉

The "context delivery system" framing hit hard. Every morning I feel like I'm running a relay race between AI tools instead of actually building.

try out our MCP server and connect to all the tools you use. The freemium is usually enough for casual users. Would love for it to be useful for you and save you some time (and headache)

This is exactly why I built MemPlato. Instead of copy-pasting

context between tools, I made a local MCP server that runs on

my Android phone – Claude connects to it and remembers everything

between sessions automatically. No cloud, data stays on device.

Launched it on PH today.

how does it ingest data? How does it organise data? How does it forget?

 Great questions!

Ingestion: You just chat with Claude – it automatically saves

key context (preferences, projects, decisions) to MemPlato

via MCP tools. No manual input needed.

Organisation: Data is stored in a "Memory Palace" structure –

wings (projects/topics) → rooms (aspects) → drawers (individual memories).

Semantic search finds relevant context automatically.

Forgetting: You simply ask Claude to forget something –

it uses MCP tools to delete or update the memory.

The LLM handles it conversationally, no manual UI needed.