AgentTeams vs LobeHub
AI agent team coordination compared
AgentTeams coordinates external agent runtimes in shared Matrix rooms, where people can observe and intervene. lobehub is a web app for building, scheduling, and organizing agents in projects and workspaces; it focuses on managing ongoing agent work in one application.
AgentTeams: Coordinate Multi-Agent Work in Matrix Rooms
AgentTeams is a collaborative multi-agent runtime platform built around Matrix rooms, where people can observe and intervene as a Manager coordinates Workers. It suits teams that want auditable agent collaboration across multiple runtimes, with local Docker setup or Kubernetes deployment.
LobeHub: Organize AI Agents for 24/7 Operations
LobeHub is a TypeScript AI-agent workspace for hiring, scheduling, and getting reports from an AI team, so work can continue while you are away. Its full-stack app uses Next.js and a Vite SPA, with self-hosting options including Docker.
| AgentTeams | LobeHub | |
|---|---|---|
| Language | Go | TypeScript |
| License | Apache-2.0 | — |
| Stars | 5.9k | 83.3k |
| Forks | 730 | 16k |
| Last analyzed | Oct 31, 2026 | Oct 20, 2026 |
Key differences
- AgentTeams uses a Manager-Workers model and Matrix rooms; lobehub offers an Agent Builder, agent groups, projects, and workspaces.
- AgentTeams runs external runtimes, including OpenClaw, QwenPaw, and Hermes; lobehub configures agents with model providers, skills, and MCP-compatible plugins.
- AgentTeams is written in Go and licensed under Apache-2.0; lobehub is written in TypeScript.
- AgentTeams offers local Docker and Kubernetes deployment, including a Helm option; lobehub supports hosted use and self-hosting with Docker or supported cloud platforms.
- AgentTeams centralizes model traffic and credentials through Higress AI Gateway; lobehub requires configuring an AI model provider and its credentials.
- AgentTeams highlights human observation and intervention in shared conversations; lobehub emphasizes scheduled runs, shared workspaces, and editable personal memory.
Choose AgentTeams if you…
- need people to observe and intervene in agent conversations through Matrix.
- want to coordinate multiple external agent runtimes under centralized credential management.
- plan to use a Kubernetes control plane with declarative team and worker resources.
Choose LobeHub if you…
- want to create and configure task-specific agents in a web app.
- need to organize agent work into projects and workspaces or schedule runs.
- want agents to collaborate using shared context, personal memory, skills, or plugins.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.