Persome

Name: Persome
Author: Intuition-Lab

by Intuition-Labversion 0.3.2i★ –iRuns on your computer

Registry nameio.github.Intuition-Lab/personal-model

Install

Overview

Description from the maker (original English)

Local-first personal memory and model server for trusted MCP agents on macOS.

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: Search & AI memory

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).
The registry lists no key to fill in.

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": {
    "personal-model": {
      "command": "uvx",
      "args": [
        "personal-model",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add personal-model -- uvx personal-model mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "personal-model": {
      "command": "uvx",
      "args": [
        "personal-model",
        "mcp"
      ]
    }
  }
}

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": {
    "personal-model": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "personal-model",
        "mcp"
      ]
    }
  }
}

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.

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 Intuition-Lab, 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 Search & AI memoryi

More stars than 0% of the other 7258 servers in this category
Published to the registry more recently than 21% of the other 7258 servers in this category
Basic checks equal to or better than 100% of the other 7258 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 Persome 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 (0.3.2) reached the registry 4 months 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: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

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

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

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.

Personal Model: local-first AI memory for coding agents

Auto-playing preview · Full-quality demo and v0.3.2 release notes

Build your HUMAN.md — one evidence-linked Personal Model for Claude Code, Codex, Cursor Agent, and other trusted MCP clients.

Personal Model is an open-source, local-first long-term memory Runtime. It learns how you think and work from focused activity captured on your Mac after you grant macOS permission, then gives your AI tools inspectable context to continue work and make grounded decisions.

Runs locally on your Mac. Private by default. Yours to inspect, correct, export, and delete.

Install Personal Model · Connect your AI tool · Star Personal Model on GitHub

_Concept illustration of a mature Personal Model._

Why Personal Model

Personal Model turns focused activity from the apps you use into a portable context layer, keeps it on your Mac, and makes it available to the trusted AI clients you choose.

One memory across agents. Connect the same Personal Model to Claude Code, Codex, Cursor Agent, and other MCP-compatible clients.
Evidence, not hidden summaries. Important claims retain source receipts; new evidence can strengthen, revise, or overturn an earlier inference.
User-owned by design. Inspect, correct, export, or delete your model and data without depending on a hosted memory service.
More than chat history. Personal Model learns from focused activity after you explicitly grant macOS permissions.

Your Personal Model is your `HUMAN.md`

Personal Model connects activity into progressively deeper context:

Layer	Meaning
Point	A sourced observation or event
Line	A relationship or change over time
Face	A pattern supported by related evidence
Volume	A higher-order structure across projects or areas of life
Root	The current integrated model of you

The result is a living model of what matters now, how you tend to decide, and where your attention is moving.

Works with Claude Code, Codex, Cursor Agent, and MCP clients

Client	Connection	Setup
Claude Code	Native Personal Model installer	`persome install claude-code`
Codex CLI and IDE extension	Native Personal Model installer	`persome install codex`
Cursor Agent CLI	Native Personal Model installer	`persome install cursor-agent`
Claude Desktop	Managed stdio config	`persome install claude-desktop`
opencode	Managed local stdio config	`persome install opencode`
Other compatible clients	Generated MCP JSON	`persome install mcp-json --filename persome-mcp.json`

The MCP client guide covers prerequisites, verification, the permission boundary, transport details, HTTP fallback, and troubleshooting.

Personal Model is an MCP server used by trusted MCP clients. Other MCP servers—such

as Filesystem, GitHub, Slack, or Google Drive—are separate tools and are not

Personal Model integrations unless that path is explicitly built and tested.

Use cases

These visuals show agent workflows enabled by Personal Model. The Runtime

supplies evidence-linked local context through MCP; connected agents own task

selection and execution, and external actions still require your authority.

1. One Root — A Model of You

Thousands of moments. One evolving model of you.

Personal Model turns sourced observations into relationships, patterns, higher-order structure, and one current Root: what matters now, how you tend to decide, and where your attention is moving.

From Points to Lines, Faces, Volumes, and one Root—a living model of who you are and what matters now.

2. Same AI. Different You.

The model is the same. The person it understands is different.

Two people can give the same AI the same prompt and deserve different answers. Your Personal Model changes how an agent prioritizes, decides, writes, and acts—because it understands who it is working for.

The same prompt should not produce the same answer for everyone. Give AI a model of you.

3. One MCP — Turn coding agents into proactive agents

Your coding agent finds its own work

Connect Personal Model once through MCP. Codex, Claude Code, and other trusted agents can use the same model of your goals, priorities, working patterns, and boundaries.

A connected agent can search Personal Model for unfinished work, rank proposed next steps against your priorities, and separate local implementation from external actions that need your approval.

Continue where you left off

Work while you sleep

Install, connect, and verify

Install Personal Model, connect a trusted MCP client, then verify the local Runtime.

1. Install with your data

Requirements: macOS 13 or newer and Xcode Command Line Tools. For the shortest package-managed installation:

uv tool install personal-model

persome onboard persome model open --after 30

The distribution is named personal-model; the installed CLI is persome.

For the most explicit source-based first run:

git clone https://github.com/Intuition-Lab/personal-model.git

cd personal-model bash install.sh

After successful interactive onboarding, the source installer opens the unified local setup experience immediately.

What onboarding proves

persome onboard explains each macOS request before it appears.
Accessibility is granted to the versioned mac-ax-helper and, only when event-driven capture is enabled, mac-ax-watcher.
Screen Recording is requested only when the effective screenshot or local-OCR policy requires pixels. Personal Model never requires Full Disk Access.
On Apple Silicon, local OCR uses bundled PP-OCRv6; on Intel, it uses the macOS Apple Vision framework. Onboarding verifies the isolated worker on both architectures.
Unified localhost onboarding offers a read-only, multi-source import and builds the first model from existing Markdown history. Local folders are always available; Obsidian and Notion appear only when detected on the Mac. The same sources remain available through persome import-data; see the import guide.
It proves the final lifecycle owner and Runtime generation, then reports a fresh-capture receipt in standard daemon mode or an explicit readiness/privacy receipt for supported alternate modes such as trusted ingest.

An LLM is optional for collection and BM25 recall, but required for semantic modeling. You can configure a hosted/local provider for unattended processing:

persome llm setup

persome llm status --check

Alternatively, explicitly lend an existing coding-agent subscription to the background Runtime. The client CLI keeps and refreshes its own login; Personal Model stores only its executable path, routing policy, and a durable daily call cap:

persome llm agent setup --client codex --daily-call-limit 50 --check

also supported: claude-code, cursor-agent

persome llm status

A trusted MCP client that supports Sampling with tools can still call process_pending_model_work for a one-request, 1–10-session batch. Both paths use the connected agent allowance without exposing its OAuth token to Personal Model; the CLI bridge is the opt-in path that also powers unattended stages.

2. Connect a trusted MCP client

persome install claude-code

persome install codex persome install cursor-agent persome install claude-desktop persome install opencode

The commands above install only the MCP server. To also give background semantic stages explicit consent to use a supported coding-agent subscription, add --fund-model; the default cap is 50 model invocations per local day:

persome install codex --fund-model --daily-call-limit 50

also supported: claude-code, cursor-agent

persome llm agent disable revokes that consent without logging the client out or deleting a fallback provider profile.

These stdio registrations launch the MCP process on demand, so the daemon does not need to be running after onboarding has initialized the local database, and no HTTP bearer is copied into client configuration. Schema creation and migration remain daemon-owned; a brand-new or externally upgraded data root must run persome start once before stdio clients use it. Stdio writes remain available while the daemon is stopped, but WAL maintenance waits for the daemon; start it periodically if you use write tools in that mode so the WAL stays bounded.

For another Cursor-compatible setup, you can still generate a stdio obj

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

Persome

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

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 Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Personal Model: local-first AI memory for coding agents

Why Personal Model

Your Personal Model is your HUMAN.md

Works with Claude Code, Codex, Cursor Agent, and MCP clients

Use cases

1. One Root — A Model of You

2. Same AI. Different You.

3. One MCP — Turn coding agents into proactive agents

Continue where you left off

Work while you sleep

Install, connect, and verify

1. Install with your data

also supported: claude-code, cursor-agent

2. Connect a trusted MCP client

also supported: claude-code, cursor-agent

Your Personal Model is your `HUMAN.md`