Statey · AI Underdogs

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AI UNDERDOGS

三个 AI，三份记忆

3 AIs, 3 Memories

Statey

你在 Claude 里建个待办

切到 Cursor 又得重来一遍

再换 ChatGPT 又是新的——三个 AI 三份记忆

谁也别想找着谁

You build a todo in Claude, then rebuild

it in Cursor, then again in ChatGPT. Three

AIs, three memories, zero coordination

一个 MCP 命令搞定

One MCP command

Statey 是个给 AI 用的共享数据库

走 MCP 协议

一行命令 mcp add mcp.statey.ai 就能在 Claude

Cursor

任何 MCP 客户端里跑起来

不用自己部署任何东西

Statey is a shared database for your AIs

It's MCP-native — one command, mcp add mcp.statey.ai

and it works in Claude, Cursor, any MCP

client. Zero infra to run

★ SIGNAL 1

每条改动都标了谁做的

Every change, tagged by who

市面上大多数 AI 记忆工具就是个黑箱

你根本不知道谁动了数据

什么时候动的

Statey 给每次改动打上标签

是你改的

Claude 改的还是 Cursor 改的

全部带版本和完整历史记录

Most AI memory tools are black boxes —

you have no idea who changed what and

when. Statey tags every mutation with the human

or agent responsible, plus version history. When three

AIs touch the same data, that's not optional

★ SIGNAL 2

不开源自部署，反而更聪明

Hosted, not self-hosted

他没走自部署开源那条路

选了托管加原生 MCP

这个判断很清醒——独立开发者为了在几个 AI 之间同步个状态

不会专门去架个数据库的

降低门槛本身就是产品决策

Instead of shipping another self-hosted open-source project, the

author went hosted plus native MCP. That's a

clear product call — solo devs won't self-host

a database just to share state between AIs

Lower barrier is the whole point

带版本的 schema

完整的历史记录

每条变更的归属——这些不是数据库炫技

是多 Agent 协作场景下真正需要解决的协调问题

目前这类工具几乎是空白

Statey 是少数在认真做这件事的

Versioned schema, full history, attribution on every change

— that's not database flexing, it's solving a

real coordination problem when multiple AIs work on

the same data. This space is still mostly

empty, and Statey is one of the few

taking it seriously

AI UNDERDOGS

一行命令，给你的 AI 们装上共享记忆

One command, shared memory for your AIs

Statey

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