OpenRig is an open-source, self-hosted coordination layer for running several terminal-based coding agents as one team. It does not replace Claude Code, Codex or their providers. It defines named roles and topology, launches and observes the agents’ tmux sessions, records coordination state in SQLite, and offers ways to restore work after interruptions. This article covers how that architecture fits together and what “persistent” does and does not mean. It is based on OpenRig’s own documentation (the docs index names version 0.5.14; the architecture page was published April 2026 and updated May 2026), so commands and counts may change in later versions.
How the pieces fit together
OpenRig’s daemon, CLI, terminal UI and MCP server share one local control plane.
- Daemon: a local HTTP service holding the domain logic and SQLite-backed state. Because state lives on disk, it survives restarts.
- CLI: the
rigcommand, used by people and by agents. It supports structured output for agent workflows. - Terminal UI: the operator’s view of topology, projects, terminals, feeds and system state. The architecture page describes an older web UI as no longer the primary surface.
- MCP server: lets MCP-capable agents operate OpenRig itself. The FAQ reports 18 MCP tools; that is a product-reported, version-sensitive count, not an independent statistic.
- tmux: every managed agent session runs inside tmux. OpenRig uses it to send input, capture output, discover sessions and retain transcripts.
The key design decision is where truth lives. The architecture documentation puts it this way: “The important word is transport. tmux is how OpenRig reaches an agent and reads what it printed. It is not where the truth lives.” Durable rig state is held in SQLite and on the filesystem, and if the database and tmux disagree, the database wins.
Vocabulary: rigs, pods, seats and sessions
| Term | Meaning |
|---|---|
| Rig | A topology of agent harnesses working together. |
| Pod | A bounded context group of related agents. |
| Seat | A named position or role that persists even when its process ends. |
| Session | The process currently occupying a seat. |
| RigSpec / AgentSpec | YAML definitions of a team topology and of an individual agent. A RigBundle can package a topology with its referenced agent specs. |
The seat/session split is what makes the model durable. A role such as “reviewer” outlives any one process, so a crashed or replaced session can be reattached to the same seat instead of the team structure being rebuilt by hand.
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The adapter boundary: management layer, not a new agent
OpenRig manages harnesses; the agents still run through their configured harnesses and provider logins. Runtime-specific behaviour sits behind adapters rather than inside the daemon. The architecture page describes adapters for Claude Code, Codex and a generic terminal runtime. The practical consequence is that your model access, quotas and agent quality remain those of the underlying tools.
Coordination: who does what, and what counts as progress
A rig definition describes roles and relationships, and rig up boots the defined sessions along with their startup material. The CLI and TUI show topology and status, and MCP-capable agents can manage OpenRig programmatically. Existing tmux sessions can be discovered and adopted rather than recreated.
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Coordination records include queue work and ownership, workflows, events and action history. The getting-started reference separates two kinds of artifact: durable scope artifacts (missions and slices, which describe what work exists) and workflow instances and queue packets (which describe who acts next). One consequence for operators: a message appearing in an agent’s terminal is not proof that work advanced. Check the resulting queue or task state.
What “persistent” means here
- tmux keeps a session alive while the machine is running.
- SQLite and filesystem records preserve coordination information across daemon or host restarts.
- Snapshots: the repository describes capturing a topology with
rig down --snapshotand restoring it by name.
Recovery can take several forms: resuming an underlying session, replaying a transcript, restoring from a checkpoint, or flagging that a seat needs attention. A failed resume is reported rather than silently presented as a fresh session. The limit is stated plainly in the FAQ: “This is not automatic full-context replication: the outcome depends on the declared continuity strategy and retained records.” Treat restoration as preserving structure, ownership and records, not as a guarantee that an agent remembers everything it knew.
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Requirements and setup cautions
- macOS or Linux, with tmux and Node.js installed (per the FAQ).
- The repository currently specifies Node.js 22 or 24, and Node.js 22 on Apple silicon Macs.
- Native Windows is not supported yet, and WSL2 has not been tested.
- Launching a rig writes provider hooks and workspace trust settings. The repository advises reading its machine-change guide and backing up relevant files before setup.
Scale and comparisons
The FAQ says OpenRig imposes no hard agent-count limit; real capacity depends on your host machine and provider subscriptions. The overview’s seven-seat product-team starter is an illustrative configuration, not a tested operating limit, and no independent capacity figure was found.
| Option | What it gives you | Layer |
|---|---|---|
| Plain terminal tabs | Parallel agents | You manage roles, handoffs and recovery manually |
| OpenRig | Named topology, retained ownership, inspection, session adoption, restore | Infrastructure managing where harnesses run |
| CrewAI, AutoGen | Orchestration defined in code | Programming framework |
These categories come from OpenRig’s own FAQ and overview. No independent benchmark of productivity or reliability against tabs or frameworks was found, so choose on fit: if your pain is losing track of who owns what across restarts, the management layer is the relevant feature.
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Evidence limits
Everything above reflects OpenRig’s published documentation and repository, not hands-on testing. Version-specific details such as tool counts and Node.js requirements should be rechecked against the current docs before you rely on them.
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