Twin Me Up

Name: Twin Me Up
Author: GitDakky

by GitDakkyversion 0.2.1i★ –iRuns on your computer

Registry nameio.github.GitDakky/twin-me-up

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: TWINMEUP_HOME

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

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

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account GitDakky, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 18323 servers in this category
Published to the registry more recently than 66% of the other 18323 servers in this category
Basic checks equal to or better than 100% of the other 18323 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Twin Me Up safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 23 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Date Math

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Only the beginning is shown; read the rest in the repo

Twin Me Up

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Date Math

README from the maker

Why

What makes it different

Compared with what you might use today

Quick start

Install with one prompt

How it works

The loop

Tools your agents get

What only you can do

Approvals