Manifold

Manifold runs live nodes on your Mac and shows them to people and agents at once. Each node publishes one value. People see it as a card on a canvas. Agents read it as text and press its actions from the command line. A manifold is a set of nodes arranged for a purpose: a trading desk, a research queue, a household.

It runs on your machine with your accounts. Other machines join by invitation and see what you grant them. No one's code runs on anyone else's machine.

This release is for macOS. Apple silicon gets the Rust door; Intel Macs run the Python door. Python 3.11 or newer.

Install

uv tool install manifold-ai

This installs the manifold command on its own, fetching Python 3.13 if your Mac has nothing new enough. uv is brew install uv. With Python 3.11 or newer already installed, pip install manifold-ai or pipx install manifold-ai do the same. A Mac's built-in python3 is 3.9, which is too old.

First manifold

manifold                         # the canvas, in your browser; the first time, it installs the core to run at login
manifold new desk --purpose "where the market stands" --section Market

manifold on its own always lands on the canvas, starting the core if it is not running. Seeing anything else means something failed, and the line says what. manifold -h is the help.

Place nodes from the library, a thousand node types in a hundred domains. manifold library lists the domains, manifold library stocks one domain's types, manifold library weather whatever matches a word; the canvas shows them as a gallery.

manifold -m desk place stocks/quote Market symbol=^GSPC name="S&P 500"
manifold -m desk approve quote   # a type that reaches outside through a tool runs once you approve it
manifold -m desk ls              # what an agent reads: every card's headline values
manifold -m desk cat quote       # one card in full

A node that needs a key asks for it by name. manifold key add stores it in the macOS keychain, and it goes only to the tool you approved it for.

Agents

Any agent with a shell works a manifold through the same commands a person uses. One run of Claude Code or Codex with Manifold as its tool:

manifold -m desk agent "say where the S&P stands and whether volatility is high" --can act

Agents that live in a manifold, with a standing task and a schedule: manifold -m desk agents new …. An agent runs only on its own machine, on your own sign-in. No machine starts an agent on another.

An agent's learning outlives its run through the memory node (manifold place agents/memory Knowledge): one fact per line, with where it came from and the day, written with do remember, revised or forgotten by id, read by the next agent on any machine the section is shared with. It is a node like any other, so grants and feeds apply to it.

A fast, typed judgment — a probability, a pick, a grade — comes from a System One model through the systemone tool and the judge node (manifold place agents/judge Knowledge). Set the tool up once on a machine: manifold key add TYPESAFE_API_KEY for TypeSafe's jev, or manifold tool set systemone provider=local url=… for a model on this machine, or provider=custom for any host that speaks the System One shape. Then any agent asks do judge ask state=… question=…, and every judgment is logged on the card with what it cost.

Working from Codex or Claude Code

Give the harness Manifold as a tool, not the raw command line:

codex mcp add manifold -- manifold mcp -m desk --can act,place,arrange     # one manifold
claude mcp add manifold -- manifold mcp -m all --can act,place,arrange     # any manifold here: the tool takes `manifold` with each command

Each session is one run with that grant: it shows on the Agents card as codex · session, every command it sends is in the activity feed, and the tool refuses whatever the grant does not cover. Approving, keys, members and the canvas stay yours, in your own terminal or in the browser. A shell inside a harness that runs manifold directly can read, and is told to use the tool for the rest. When you ask the agent to show you the canvas, its canvas command opens it in your browser on this machine; the agent gets no address.

Talking to a manifold

With an xAI or OpenAI key on the machine, a person can talk to a manifold from the canvas and have the voice work it:

manifold key add XAI_API_KEY
manifold -m desk voice on can=act,place,agents            # provider=openai model=… voice=… choose who answers

Press Talk on the canvas. The voice is an agent like any other: a run with the grant you gave, every command in the feed, the one manifold tool, and agent to start Claude or Codex on a longer task when agents is in the grant. Approving, keys and members stay yours: the voice asks, you press. The browser does the microphone and speaker; the key never leaves the core.

Other machines

A manifold runs on one machine. Any other machine, yours or a friend's, joins with a one-time invitation:

manifold -m desk share --role build       # on the machine the manifold lives on: prints an invitation
manifold join mf2.…                       # on the other machine

Roles: read (ls, cat), act (also press actions), build (also place, set, move and remove nodes). Approving, inviting and keys never leave the machine the manifold runs on. A private section is invisible to everyone you share with until you open it to one of them by name:

manifold -m desk private Account
manifold -m desk members allow "MacBook Air" Account

Your devices keep a copy of what they may see, so they can read the manifold while the machine it runs on is off.

Where things are

The package contains code, the node library with synthetic sample data, and the door binary; nothing from the machine it was built on. Everything you make lives in your home folder. A key goes to the macOS keychain, never to a file. Nothing leaves your machine except what you grant to a machine you invited, through the door.

Building a node

A node is three files. node.json says what it answers, its settings and the shape of its value. node.py has gather(m, s), which returns the value, and act_<name>(m, s, …) for each action. view.html draws the card. manifold bench <folder> --save --shot runs one without a core. library/GUIDE.md is how library nodes are built.

Development

git clone … && cd manifold && uv venv --python 3.13 && uv pip install -e ".[dev]"
(cd door && cargo build --release)          # the door; without it the Python door runs
.venv/bin/python -m pytest -q

DECISIONS.md holds every design decision with its reason and what would prove it wrong. AUDIT.md records what a hostile machine was tried against and what remains unproven. Apache-2.0.