knowledge

Name: knowledge
Author: To0wnn

by To0wnnversion 0.37.5i★ –iRuns on your computer

Registry nameio.github.To0wnn/knowledge

Install

Overview

Description from the maker (original English)

Self-hosted shared memory and docs for Claude Code, Codex and Antigravity agents, with a graph UI

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: Streamable HTTP
Category: Search & AI memory
You need to fill in: KNOWLEDGE_UI_PASSWORD

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: KNOWLEDGE_UI_PASSWORD, KNOWLEDGE_ALLOWED_HOSTS

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

DockerDocker installed

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": {
    "knowledge": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "KNOWLEDGE_UI_PASSWORD",
        "-e",
        "KNOWLEDGE_ALLOWED_HOSTS",
        "ghcr.io/to0wnn/knowledge:0.37.5"
      ],
      "env": {
        "KNOWLEDGE_UI_PASSWORD": "your-value",
        "KNOWLEDGE_ALLOWED_HOSTS": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add knowledge --env KNOWLEDGE_UI_PASSWORD=your-value --env KNOWLEDGE_ALLOWED_HOSTS=your-value -- docker run -i --rm -e KNOWLEDGE_UI_PASSWORD -e KNOWLEDGE_ALLOWED_HOSTS ghcr.io/to0wnn/knowledge:0.37.5

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": {
    "knowledge": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "KNOWLEDGE_UI_PASSWORD",
        "-e",
        "KNOWLEDGE_ALLOWED_HOSTS",
        "ghcr.io/to0wnn/knowledge:0.37.5"
      ],
      "env": {
        "KNOWLEDGE_UI_PASSWORD": "your-value",
        "KNOWLEDGE_ALLOWED_HOSTS": "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": {
    "knowledge": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "KNOWLEDGE_UI_PASSWORD",
        "-e",
        "KNOWLEDGE_ALLOWED_HOSTS",
        "ghcr.io/to0wnn/knowledge:0.37.5"
      ],
      "env": {
        "KNOWLEDGE_UI_PASSWORD": "your-value",
        "KNOWLEDGE_ALLOWED_HOSTS": "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

KNOWLEDGE_UI_PASSWORD secret required env
Password for the web UI (admin page, device tokens)
KNOWLEDGE_ALLOWED_HOSTS env
host:port values clients may use

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account To0wnn, 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 7248 servers in this category
Published to the registry more recently than 100% of the other 7248 servers in this category
Basic checks equal to or better than 100% of the other 7248 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 knowledge 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?

You need to fill in: KNOWLEDGE_UI_PASSWORD

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 (0.37.5) reached the registry today.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker 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.

knowledge

Your coding agents share one memory and hand work to each other across your own PCs — and you steer them from your phone. Self-hosted, plain Markdown.

Works with Claude Code, Codex and Antigravity (agy, Gemini) on Linux, macOS and Windows. Made for solo developers and homelabbers with two or more PCs and two or more agents who want their notes to stay on their own server.

One memory, every agent. Tell Claude Code something on your laptop; Codex on your desktop knows it. Notes are plain Markdown files on your disk, found by meaning (98.8% R@5 on LongMemEval-S, embeddings run locally).
Agents hand work to each other. One line in a note hands a task to another agent; it runs once, on one of your PCs, in its own git branch, and the result comes back to whoever asked.
You steer from your phone. An inbox of what needs you, chats with the agents on your PCs, and Allow/Deny for each risky step, in a web app you install on your phone.

Made-up demo notes from demo/ .

You can use it in two layers. Memory is the server plus one agent: five minutes, nothing else on your PCs. Cockpit adds the companion on each PC, so tasks run as workers and you can chat and approve from your phone.

Quickstart: Memory

You need Docker and about 2 GB RAM on the server, and git plus Python 3.9 or newer on each PC.

1. Run the server.

git clone https://github.com/To0wnn/knowledge && cd knowledge

mkdir data && echo "KNOWLEDGE_UI_PASSWORD= " > .env docker compose up -d

2. Get the first token. The first start makes one admin token and prints it once, with the next steps:

docker compose logs knowledge

Tokens for more devices: open http://localhost:8766/ui, sign in with the password and use the admin page (Admin); it shows the install line with your server address filled in.

3. Connect an agent on the same PC:

curl -fsSL https://raw.githubusercontent.com/To0wnn/knowledge/main/install.sh | sh   # Linux, macOS

irm https://raw.githubusercontent.com/To0wnn/knowledge/main/install.ps1 | iex        # Windows

It finds Claude Code, Codex and agy, asks y/n for each, and asks for the server address (http://localhost:8766) and the token. Run the same line again later to update. Only the plugin, without the companion (a work laptop, an SSH server): add -s -- --plugin-only after sh (docs/clients.md).

4. Try it. Tell Claude Code: *"save to knowledge: we deploy with ./deploy.sh"* (the installer turns Claude's own local auto-memory off, so it writes a memo on the server). Then start Codex (or agy), on this pc or another, and ask *"how do we deploy?"*. It answers from the shared memory.

More than one PC? Put the server behind HTTPS (a reverse proxy) and add its host:port to KNOWLEDGE_ALLOWED_HOSTS in .env; then run the install line on every PC with a token per device. Over plain HTTP the password and tokens cross the network readable. All settings: docs/server.md.

Add the Cockpit

The install line also sets up the companion, a small local service on each PC (127.0.0.1:47321, starts at logon). With it:

Workers. A task handed to an agent runs as a fresh headless session in its own git worktree and branch, at most one per agent by default, paused at 90% of the agent's usage limit. Workers are off until you tick "Workers allowed" on the companion's page. Follow a worker to watch it live in the chat view, steer it between steps, or take it over as a chat. docs/tasks.md
Chats from your phone. Open the web UI on your phone and install it as an app; start a chat with Claude Code, Codex or agy in a project folder on one of your PCs. The answer streams in as in a terminal. Attach files or screenshots, or speak your message (any OpenAI-compatible speech-to-text server, one is bundled). docs/chats.md, docs/voice.md
Approvals. Without YOLO, an agent in a chat may edit files in its folder and asks you for anything else: Allow once, Allow for this chat or Deny, on the phone or in the Inbox. docs/chats.md
Inbox and Machines. One board of what needs you, what runs and what is done; per PC its agents, workers, usage and a fixed set of remote actions (no remote shell). docs/companion.md

To use it from your phone, the server must be reachable from the phone over HTTPS. Link a project folder once by asking your agent to run the skill knowledge-init.

Compared with

Each of these is good at its own part; knowledge is the one that combines shared memory, hand-overs and a phone cockpit across several agents and PCs.

Tool	What it does well	Where knowledge differs
claude-mem	Automatic session memory for Claude Code, local	One server for Claude Code, Codex and agy on all your PCs; plain Markdown you edit
basic-memory	Local Markdown knowledge base over MCP	Adds shared multi-PC serving, house-rule lint, duplicate checks and agent hand-overs
Happy, Omnara, Claude Code Remote Control	Steer a running agent session from your phone	Also memory and tasks between agents; self-hosted, no third-party relay
Conductor, Superset	Run parallel agents in worktrees on one Mac or desktop	Workers on any of your PCs (Linux, macOS, Windows), started from a shared task list
Vibe Kanban	Kanban board that runs coding agents in worktrees	Tasks are lines in your notes, agents hand them to each other, steered from the phone

Honest limits

A server to run: Docker, about 2 GB RAM, an image of about 1.5 GB (the embedding model ships in it).
HTTPS for more than one PC or the phone: you put a reverse proxy in front.
Agents: Claude Code, Codex and Antigravity (agy) only.
Notifications: a Matrix room or an ntfy topic (set a few values in .env) and desktop notifications in an open browser tab; no phone push without one of those (docs/server.md).
One admin: password sign-in is for one person; several people need a reverse proxy with forward auth.
One maintainer, built for their own use first. Issues and pull requests welcome.

Known gaps: docs/ROADMAP.md.

How it works

Server (server/): Python in one Docker container, MCP over streamable HTTP plus the web UI. All notes sit in memory; search and embeddings (EmbeddingGemma, ONNX) run locally, nothing leaves the machine.
Notes: plain Markdown in data/, with a MEMORY.md index per project, a few house rules and a lint that keeps agent memory findable and free of duplicates.
Plugin (plugin/): one folder that installs in Claude Code, Codex and agy: the MCP server, session-start context, hand-over checks each turn, and development skills. Tokens live in the OS keyring.
Tasks: a hand-over is a line in a note (- open until [ , ] from , start ...: ); the server decides when it may start and gives it to one machine only.
Companion (clients/, plugin/companion): pulls tasks, actions and chat messages from the server; the server never connects to your PCs.

Documentation

Page	Contents
server.md	Running the server, `.env` settings, proxy sign-in, notifications
clients.md	The installer, updates, linking folders, Windows, skills, usage limits, secret guard
memory.md	MCP tools, session start, projects, lint, duplicates, secrets, search quality
tasks.md	Task lines, leases and nonces, results, workers, usage limit, mission map
companion.md	The companion, machines, own devices, remote control, YOLO safety
chats.md	Agents (what needs you, what runs, chats) and approvals
voice.md	Speaking chat messages: set up speech to text
web-ui.md	Views, routes, graph, installing as an app (PWA, cookies)
security.md	The security model in one page
development.md	Tests, CI, plugin versions, screenshots
ROADMAP.md	Known gaps

License

MIT, see LICENSE.

The server image includes the EmbeddingGemma model weights. Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms; its use is also subject to the Gemma Prohibited Use Policy. The weights are not modified.

knowledge

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 Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

knowledge

Quickstart: Memory

Add the Cockpit

Compared with

Honest limits

How it works

Documentation

License