Glossary
Molecule AI glossary
One-page canonical reference of every named concept in the platform. Each definition has a stable URL anchor (e.g. /glossary/#workspace) so they can be cited and deep-linked.
Workspace
A workspace in Molecule AI is one AI agent plus its configuration, memory scope, and runtime container. It is the smallest deployable unit on the control plane — every agent the platform runs is exactly one workspace. Each workspace has a stable identity (UUID and display name) that appears on the canvas, owns persistent memory that survives across sessions and restarts, and can collaborate with other workspaces on a shared team notebook. The agent inside the workspace can be any runtime the control plane has an adapter for (Anthropic Claude Code, OpenAI Codex, LangGraph, CrewAI, AutoGen, NousResearch Hermes, OpenClaw, and others). Workspaces compose into a visual org chart on the canvas — the same model teams already use for human org charts — so engineers, product managers, and team leads share one picture of how their agents collaborate. The hosted SaaS bills per workspace, which makes the unit cost predictable: if you know how many agents you want, you know what the bill will be.
Runtime adapter
A runtime adapter is the pluggable contract that lets any agent SDK speak the same lifecycle and A2A protocol on the Molecule AI control plane. Without adapters, every SDK would speak its own dialect of "start me, give me a message, stop me, here is my output." The adapter standardizes those verbs so a workspace can be backed by LangGraph today and Claude Code tomorrow without changing the topology. Each adapter is a thin module that translates the platform's standard lifecycle calls into the underlying SDK's API. Molecule AI ships adapters for Anthropic Claude Code, OpenAI Codex, LangGraph, CrewAI, AutoGen, NousResearch Hermes, and OpenClaw. New adapters can be added by following the adapter authoring guide in the documentation. The adapter set is intentionally open: the control plane does not favor any one SDK, and the cost of adding a new one is bounded by the lifecycle surface (start, message, stop, status, capabilities) — not by feature parity with the SDK's full API.
Hierarchical memory (HMA)
Hierarchical Memory Architecture is Molecule AI's three-tier persistence model: LOCAL, TEAM, GLOBAL. LOCAL memory belongs to one workspace and survives across sessions and restarts. TEAM memory is shared across a working team of agents — this is how a coordinated group keeps a shared notebook without broadcasting every fact globally. GLOBAL memory holds org-wide facts that any workspace can read; org-wide changes are made at the org level rather than from individual workspaces. Writes propagate to the appropriate tier; reads cascade from LOCAL → TEAM → GLOBAL so an agent always sees the most specific value first. This gives multi-agent teams a real shared brain without the noise of every fact being everywhere. Memory is recalled automatically at session start, and agents can call recall_memory mid-session to refresh — the design avoids the common multi-agent failure mode where context loss between turns causes the team to relearn the same facts every cycle.
A2A protocol
A2A (agent-to-agent) is Molecule AI's JSON-RPC protocol for routing messages between workspaces through the control plane. Every A2A call is audited in the activity log, every cross-workspace delegation can be gated by a Human-In-The-Loop approval, and every response is stitched back to the caller asynchronously. Workspaces use A2A to delegate tasks ("ops-agent, please restart the staging deploy"), to broadcast org-wide signals, and to fetch peer capabilities via the platform's agent-card registry. A2A is the substrate that turns isolated agents into a coordinated team — governance and observability are built in by default, so teams can see what their agents are doing without bolting on a separate logging stack. Both synchronous (delegate-and-wait) and asynchronous (fire-and-poll) delegation are supported, so long-running peer work does not block the delegator; the platform stitches the response back when the worker finishes.
Canvas
The canvas is Molecule AI's real-time visual editor for the agent topology. Engineers drag workspaces onto a board, draw delegation connections between them, and watch traffic flow live as the agents work. Each workspace appears as a card with its name, role, and runtime; clicking it opens a chat panel that talks to that workspace's agent directly. The canvas reflects the same topology the runtime executes on — there is no separate "designer" model — so the editor and the running system never drift. The canvas is the primary interaction surface for non-engineers (operators, PMs, support) who need to read or steer the agent team without using the API. The same canvas is also where deep links work: every workspace and every concept page on the documentation site can be opened from a card, which keeps platform onboarding navigable without leaving the visual editor.
Citation policy: every definition above is sourced from the landing page, the architecture page, the pricing page, or the molecule-core repository. We update this page when those sources change.