LobeChat

Most agents today are one-off tools: no shared context, no memory worth the name, and constant manual hand-offs between windows and models. LobeHub answers that by treating agents as the unit of work, giving them a space where they are hired, scheduled and reported on like teammates.

Building one starts with the Agent Builder. You describe what you need once and the setup runs immediately, applying auto-configuration so the agent is usable straight away. Agents reach any model and any modality, and connect to a library of more than ten thousand tools and MCP-compatible plugins.

Collaboration is where the model of a team gets exercised.

• Agent Groups: the system assembles the right agents for a task and lets them work in parallel.
• Pages: several agents write and refine content together in one shared context.
• Schedule: runs happen at the right time, including while you are offline.
• Workspace: a shared space with clear ownership and visibility across an organization.
• White-box memory: structured, editable memory that you can inspect and correct.

Self-hosting comes as a Docker image or a one-click deployment on Vercel, Zeabur, Sealos or Alibaba Cloud, with an OpenAI API key supplied as an environment variable. LobeHub is under active development, so expect the feature list to keep moving.