Free runs on your machine
init, sync, doctor, and core MCP tools stay local. No card required to try a real repo.
0dai keeps the roadmap, rules, and review receipts in your repo's ai/directory — so every CLI works under the same rules and every run leaves a receipt you can replay.6 terminal CLIs + Cursor MCP bridge
projects initialized
terminal CLIs
registered MCP tools
Works with your favorite AI coding agents
I built 0dai because I was tired of explaining my repo for the 47th time. Every new chat, every new agent, the same setup tax. The agents were not dumb — they were amnesiac. So I made the memory layer they should have had.
47th time explaining the repo. Ragequit. Opened editor.
Safety rails + ai/ scaffold. First dogfood task shipped.
Working group v2.2 · 6 deliberation profiles.
Ghost peer-critic · 2-of-3 consensus. Race caught before merge.
700+ tests. v4 CLI. Friday digest cadence running.
Dogfooded on its own repo, every change with receipts.
for solo founders
You ship alone. You should see the bill before checkout and own the repo if 0dai stops tomorrow. No black-box memory, no hostage data.
init, sync, doctor, and core MCP tools stay local. No card required to try a real repo.
Seat price and token estimates live on the pricing page with a calculator. No surprise invoice after a trial.
0dai export --all writes a tarball you can inspect. Today it includes personas, path-protect policy, and usage ledger when present; remaining surfaces are labeled in progress.
Not a fit for every team. See where Claude Code subagents beat 0dai — the honest feature matrix.
raw graph access would commoditize the product. subscribers get curated bulletins and routing data instead.
safety rules, governance, agent-config templates, master-plan scaffold, onboarding ritual. Installs into your repo and stays.
cross-project pattern library, model-routing data, security bulletins, and agent capability benchmarks.
architectural-consistency rules, tier-aware agent configurations, and advanced governance.
not a screenshot gallery. graph viewer, master plan, and doctor are the operational surfaces users inspect.
The prototype makes invisible agent work visible: memory load, routing, consensus, patch hold, QA proof, and outcome capture.
Load local decisions and promoted patterns before code changes.
Pick the model that wins this task class this week.
Surface blockers before they become a bad merge.
0dai init --local writes a CLAUDE.md / AGENTS.md scaffold with no signup. A free, no-card account adds the full per-CLI config set, sync, and run.
Install the CLI globally from npm.
Write the scaffold with one command. No account needed.
Free, no card. Adds the full per-CLI set, sync, and run.
Hand a real goal to 0dai run "..." --now and read the receipt.
Ship one real change and capture the outcome.
No long manual. These five cover install-to-first-task. Each is the same line you will find in the README.
create ai/ layer, auth, and MCP bootstrap
run one task locally now, get a scored receipt — no account
health check for credentials, drift, and env
maturity, swarm tasks, and session state
refresh ai/ after repo or server changes
Cancel Pro and you keep what is already in your repo. The cloud layer goes dark. No bait, no decay of local code.
Estimate a monthly bill from PR volume, agent count, token budget, and runner choice.
Monthly estimate
$50
Estimates use transparent unit assumptions; final invoices follow authenticated account metering.
No. Native configs are the entry point. The value is the living memory, routing, outcomes, and gates around the agents.
The free local workflow keeps source local. Product metadata, manifests, and promoted patterns are the cloud boundary.
The concept is explicit: free stays free, Pro is for the network, Team is for shared operational memory.