Twin Me Up

Name: Twin Me Up
Author: GitDakky

作者：GitDakky版本 0.2.1i★ –i在你的电脑上运行

注册名称io.github.GitDakky/twin-me-up

安装

概览

作者提供的说明（英文原文）

A personal work twin for every AI agent: your confirmed guidance and explicit grants, enforced.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 其他

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
需要你自己填写： TWINMEUP_HOME

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "twin-me-up": {
      "command": "uvx",
      "args": [
        "twin-me-up"
      ],
      "env": {
        "TWINMEUP_HOME": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add twin-me-up --env TWINMEUP_HOME=your-value -- uvx twin-me-up

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "twin-me-up": {
      "command": "uvx",
      "args": [
        "twin-me-up"
      ],
      "env": {
        "TWINMEUP_HOME": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "twin-me-up": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "twin-me-up"
      ],
      "env": {
        "TWINMEUP_HOME": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

TWINMEUP_HOME env
Directory holding your twin. Defaults to ~/.twinmeup. Run `twinmeup init` there first.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 GitDakky 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 18329 个服务器的 0%
发布到注册中心的时间比此分类中其他 18329 个服务器的 66% 更新
基础检查结果等于或优于此分类中其他 18329 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Twin Me Up 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.2.1）于23天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, Excaliself

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者：formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新

安装

Remote Desktop Commander

作者：desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新

安装

Excaliself

作者：maciekzygmunt

Find, read, create, edit, and organize Excalidraw drawings in your self-hosted Excaliself instance.

在云端运行今天更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Teach it once. Every agent you use works the way you would, and asks before it acts.

Quick start · One-prompt install · How it works · Works with · The research · Safety

Why

You probably use more than one AI agent. Each one starts from zero. It does not know what you care about, which corners you never cut, or which decisions you always want to make yourself. So you repeat yourself, correct the same mistakes, and hope nothing consequential happens before you look.

Twin Me Up is a small, local, open-source service that gives every agent the same answers to three questions:

How does this person want this kind of work done? Your confirmed guidance, criteria, exceptions and red lines, briefed to the agent at the start of work.
Am I allowed to do this? Explicit grants, scoped to a workflow and a set of actions, with optional expiry. Anything not granted returns ask. Optional hooks enforce that outside the model.
What did I just learn? Your decisions and corrections become candidate lessons. Only you can confirm them.

It is not a chatbot of you, a personality clone or an autonomous replacement for you. The evidence does not support those claims, and the research explains why.

What makes it different


Learning you ratify	Agents propose lessons. Only you confirm, revise, reject or retire them. Every lesson keeps its origin, sources and history.
Authority you grant	Agents act on explicit grants for a workflow and named actions, optionally expiring. Actions in the reserved `twin.` namespace can never be granted to anyone.
Enforcement outside the model	Pre-action hooks for Hermes, Claude Code and pi block or escalate ungranted tool calls. They fail closed.
Evidence, not vibes	Freeze held-out decisions, then test the twin against a generic assistant and a rules-only baseline. Results come with sample-size warnings.
One twin, every agent	One MCP server, a native pi extension, a CLI bridge and function-calling schemas. Thirteen agent systems and frameworks documented, ten verified live.
Yours	Local SQLite with owner-only files, a tamper-evident audit log, portable export, and erasure that removes everything derived from a record. No telemetry.

Compared with what you might use today

	A rules file or system prompt	Built-in agent memory	Twin Me Up
Works across every agent you use	Copied into each one	Within one product	One twin, over MCP
Learns from your corrections	No	Often, automatically	Yes, as proposals
You approve what it learns	You write all of it	Usually after the fact	Always, before it counts
Stops actions you have not allowed	No	No	Yes: grants, `ask` and hooks
Shows whether it actually helps	No	No	Held-out tests against baselines
Where your data lives	Your files	The vendor	Your machine

Quick start

You need Python 3.11 or later and uv (or pipx). macOS and Linux are tested. Windows should work but is untested.

uv tool install twin-me-up        # or: pipx install twin-me-up

twinmeup init # your name and a passphrase, in your own terminal twinmeup connect --list # every supported agent system twinmeup connect claude-code # the exact steps for one of them, with your paths twinmeup doctor # check everything, including a live MCP handshake

twinmeup init asks for your name and a passphrase. The passphrase guards everything only you should do: confirming lessons, granting authority, exporting and erasing. Agents are never given it, and those commands refuse to run without it.

Only need the MCP server? After twinmeup init, any MCP client can start it with uvx twin-me-up. Prefer the latest code? uv tool install git+https://github.com/GitDakky/twin-me-up.

Upgrading? Run uv tool upgrade twin-me-up (or pipx upgrade twin-me-up), then twinmeup doctor. The FAQ explains what an upgrade changes for your twin.

Using Claude Desktop? After twinmeup init, download the .mcpb desktop extension from the latest release and open it. One bundle works on macOS, Windows and Linux.

Install with one prompt

Already working inside an agent? Paste this into it.

Copy-paste install prompt

Install Twin Me Up for me and connect it to yourself. Twin Me Up is a local, open-source

work twin: it learns how I make decisions, briefs you at the start of work and tells you when you need my approval. Repository: https://github.com/GitDakky/twin-me-up

Work step by step and show me each command you run.

Install it. Prefer uv: uv tool install twin-me-up If uv is not available, use pipx: pipx install twin-me-up If PyPI cannot be reached, install from GitHub instead: uv tool install git+https://github.com/GitDakky/twin-me-up Then check with: twinmeup version

Ask me to run twinmeup init myself, in my own terminal, and wait until I say it is done. It sets my name and a passphrase that only I know. Do not run it for me, do not ask me for the passphrase, and never type a passphrase anywhere.

Run twinmeup connect --list, pick the entry that matches you (or generic), then run twinmeup connect and carry out the steps it prints to register the MCP server and install the skill. If it offers optional enforcement hooks, show me the action map and the hook configuration first, and install them only if I agree.

Run twinmeup doctor and report the result.

If your system needs a new session to load MCP tools, tell me. Otherwise call twin_brief for workflow "general" and summarise what it says.

While you work with my twin:

Call twin_brief at the start of a piece of work.
Call twin_authorise before anything consequential: sending, paying, publishing, deleting or committing on my behalf. If the answer is "ask", prepare a draft, request my approval with twin_request_approval, and act only once twin_approval_status says it is approved.
Give every write a request_id, so a retry never records anything twice.
When I correct you, record it with twin_record_correction.
Never try to confirm lessons, approve requests, grant authority, export or erase. Those are mine, and the twin will refuse you anyway.

The agent installs the package, connects itself and checks the result. The two steps that matter stay with you: choosing the passphrase, and approving any enforcement hooks. The prompt is also in docs/install-prompt.md.

How it works

flowchart LR

you([You]) twin[("Your twin local store")] agent["Any agent"] hook{{"Pre-action hook"}} you -- "confirm lessons grant and approve" --> twin twin -- "candidate lessons to review" --> you agent -- "twin_brief twin_authorise request approval" --> twin agent -- "record decisions and corrections" --> twin agent -. "every governed tool call" .-> hook hook -- "ungranted: block or ask" --> agent hook -- "checks grants" --> twin

The loop

Orient. At the start of work the agent calls twin_brief. It gets your confirmed guidance for the workflow, with boundaries and escalation rules always included, and a list of what it is authorised to do.
Check. Before anything consequential it calls twin_authorise. The answer is allow only when a live grant covers the action. Otherwise it is ask: the agent prepares a draft, requests your approval and waits for your decision.
Learn. When you make a decision or correct the agent, it records the decision or the correction and proposes lessons from it.
Ratify. You review the queue and confirm, revise or reject each lesson. Only confirmed lessons reach future briefs.
Prove. You freeze held-out decisions and test the twin against two baselines before trusting it with more.

Tools your agents get

Tool	What it does
`twin_brief`	Your confirmed guidance and current authority for a workflow. Call it at the start of work.
`twin_authorise`	May I do this now? Returns `allow` with the covering grant, or `ask`.
`twin_request_approval`	Ask you to approve one action. You decide in your own terminal.
`twin_approval_status`	Has the request been approved, declined or not yet decided?
`twin_search`	Find confirmed guidance relevant to a question.
`twin_review_queue`	Unconfirmed lessons to show you for review.
`twin_track_record`	Evidence and stage for a workflow: learning, corrections, evaluations and grants.
`twin_next_questions`	The most valuable unanswered questions about a recorded decision.
`twin_record_decision`	Capture a real decision: situation, options, choice, reasons.
`twin_amend_decision`	Merge your answers to follow-up questions into a recorded decision.
`twin_record_correction`	Record when you edit, override or reject the agent's work.
`twin_propose_lesson`	Propose a lesson. It has no authority until you confirm it.

What only you can do

These commands need your passphrase, so agents cannot run them.

Command	Purpose
`twinmeup init`	Set your name and passphrase
`twinmeup lesson confirm`, `reject`, `revise`, `retire`	Decide what your twin has learned
`twinmeup grant add`, `revoke`	Give or withdraw authority
`twinmeup approvals approve`, `decline`	Decide what agents have asked to do
`twinmeup eval create`, `add-case`, `from-episode`, `freeze`	Build held-out evaluation sets
`twinmeup export`	Write a portable bundle of your twin
`twinmeup erase episode`	Erase a decision and everything derived from it

Approvals

An agent that needs an action it has not been granted asks for it, then waits:

twin_authorise says ask. The agent prepares a draft and calls twin_request_approval with a one-line summary of what an

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