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 new desk --purpose "where the market stands" --section Market
manifold service install # the core runs at login and stays up; or run it now with: manifold core
manifold open # the canvas, in your browser
Place nodes from the library, a thousand node types in a hundred domains. manifold library lists them; 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.
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
| your manifolds, keys' names, feeds | ~/.manifold (or MANIFOLD_HOME) |
| a manifold | a folder: layout.json, nodes/<type>/ (node.json, node.py, view.html), docs/ |
| the node library | shipped in the package; MANIFOLD_LIBRARY points elsewhere |
| the door | the process that carries connections between machines (Rust; door/ in the source) |
| the canvas | http://127.0.0.1:8730 |
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.
Metadata
Release files for manifold-ai 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| manifold_ai-2.0.0.tar.gz | 12.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| manifold_ai-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 28.2 MB
Release files / manifold_ai-2.0.0.tar.gz
| Download URL | manifold_ai-2.0.0.tar.gz |
|---|---|
| Size | 12.9 MB |
| Tags | Source |
|
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Release files / manifold_ai-2.0.0-py3-none-any.whl
| Download URL | manifold_ai-2.0.0-py3-none-any.whl |
|---|---|
| Size | 15.3 MB |
| Tags | Python 3 |
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twine/7.0.0 CPython/3.13.3
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