What is WarmHub?

WarmHub is knowledge infrastructure for AI agents — a platform purpose-built so that what agents learn persists, compounds, and stays yours. Think of it as what GitHub did for code, applied to knowledge: versioned, attributed, auditable, and shareable.

Why WarmHub?

Traditional databases store rows. WarmHub stores claims about the world — versioned, attributed, and queryable. Every write creates version history. Every entity carries its full history. Every assertion knows what it’s about.

What sets WarmHub apart is its native support for beliefs — assertions carry confidence, evidence, and attribution, making it possible to model what an agent thinks it knows, not just what it recorded. Multiple agents can hold different beliefs about the same thing, and the system preserves all of them with full provenance. Knowledge compounds across sessions, agents, and teams — each agent builds on what previous agents learned.

This makes WarmHub ideal for:

• AI agent memory — Agents write observations, beliefs, and decisions as structured assertions. Knowledge persists across sessions, so agents don’t start from zero every time.
• Multi-agent coordination — Multiple agents working on the same problem write to a shared repo. Each version is attributed, so you can trace who said what and when.
• Calibrated uncertainty — Model confidence, evidence, and competing perspectives as first-class data. Assertions from different agents coexist — you can compare, reconcile, or let them evolve independently.
• Auditable knowledge bases — Every version of every entity is preserved. You can always ask “what did we know at time T?” or “who changed this and why?”

Key Design Principles

Everything is versioned. Things, assertions, and shapes all produce new versions on every change. Old versions are never deleted.

Names are stable, not permanent. Names identify things and appear in wrefs (references like Shape/name), but they can be changed. When a thing is renamed, existing references automatically resolve to the new name. Things are linked by identity, not by name — the name is a human-readable label on top of that link.

Agents are first-class. WarmHub exposes an MCP server so AI agents can read and write data using the Model Context Protocol. The wh prime command gives agents a complete context dump in one call.

How to Get Started

Start with Core Concepts to understand the mental model — orgs, repos, shapes, things, assertions, and writes. Then pick the interface that fits your use case:

	SDK	CLI	MCP
Best for	TypeScript apps, custom agents, programmatic access	Terminal exploration, shell scripts, quick operations	AI agents with MCP-compatible clients
Type safety	Full TypeScript types	JSON output via --json	Tool schemas
Setup	npm install + client constructor	npm install -g @warmhub/cli	Configure MCP endpoint
Write pattern	client.commit.apply(...) or OperationBuilder	wh commit submit ...	warmhub_commit_submit tool
Read pattern	client.thing.head(...)	wh thing list	warmhub_thing_head tool
Real-time	client.live.subscribe(...)	wh thing list --live	Claude Code only, via wh channel (research preview)
Get started	SDK Quickstart	CLI Quickstart	Connect MCP

All three interfaces share the same backend and concepts — shapes, things, assertions, writes, and wrefs.