openrig vs Ruflo: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of openrig and Ruflo — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
o
openrig
mvschwarz
OpenRig is open-source software to define a team of Claude Code and Codex agents in YAML and run them as one persistent, managed system.
Key features
- YAML Rig Definitions: Describe an agent team with roles in YAML and boot it with a single command.
- Mixed Harnesses: Run Claude Code and Codex agents together in the same rig, managed as one system.
- Lead Agent Coordination: Talk to a lead agent that coordinates specialists across teams and reports back decisions needing attention.
- Persistent Teams: Keep team work and context at stable addresses instead of a pile of terminal sessions.
- Terminal UI: View the rig as a graph or a table of seats showing runtime, model, context and state, with per-seat detail.
- Guided First Use: A getting-started path installs, launches a two-agent team in your repository and produces one reviewed change.
- Permission Allowances: Optionally lets your agent add scoped native rules so OpenRig commands run without repeated prompts, with an undo.
- CLI Install: Distributed as @openrig/cli on npm, requiring Node.js 22 or 24 and tmux on macOS or Linux.
Best for
- Multi-Agent Coding Teams: Stand up a persistent team of coding agents with defined roles for a repository.
- Cross-Harness Workflows: Combine Claude Code and Codex strengths within one coordinated team.
- Outcome-Driven Delegation: Describe a desired outcome to a lead agent and let it split work among specialists.
- Agent Monitoring: Watch seats, models, context and state of many agents from one terminal UI.
- Reviewed Changes: Have agents produce a change in a repo and another review it before you merge.
- Agent Research Experiments: Prototype and study networks of cooperating agents on your own machine.
R
Ruflo
rUv (ruvnet)
Open-source agent meta-harness for Claude Code and Codex adding swarms, self-learning memory, MCP tools and security guardrails.
Key features
- Agent Swarms: Over 100 specialized agents self-organize into coordinated swarms to split up and run complex tasks.
- Self-Learning Memory: Remembers across sessions and learns from successful trajectories using local vector retrieval and contrastive updates.
- MCP Server: Run npx ruflo mcp start to expose Ruflo's tools to Codex or any MCP-enabled client.
- Claude Code Plugins: Core tools, a visual console and runtime mods add routing and policy enforcement inside Claude Code.
- Terminal UI Console: Shows Overview, Cost, Swarm, Events and Missions pages, and also runs standalone.
- Federation: Lets agents on different machines communicate securely without leaking data.
- Hook-Based Routing: Hooks automatically route tasks and coordinate agents in the background.
Best for
- Large Refactors: Split a big codebase change across a swarm of specialist agents.
- Persistent Project Context: Keep knowledge across Claude Code sessions with vector memory.
- Multi-Client Setups: Connect Codex or other MCP clients to the same tool server.
- Cost Monitoring: Track spend and agent activity from the console during long runs.
- Multi-Machine Collaboration: Let agents on separate machines coordinate through federation.