LobeHub vs Onyx
Two of the top chat uis, side by side: score, setup, license, activity and what each review found.
LobeHub
Agent workspace with builder, groups, scheduling and 10,000+ MCP skills
Onyx
Team knowledge chat that indexes 50+ apps for RAG and agents
| What we compare | LobeHub | Onyx |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 86, widely used | 58, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 83, healthy | 83, healthy |
| Easy to run | 83, very easy | 50, easy |
| Agent-ready | 45, minimal | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 83.2k | 32.4k |
| License | custom license (read the license) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Not stated | Not stated |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Mentioned |
LobeHub
LobeHub is a self-hostable agent workspace that runs on Vercel, Zeabur, Sealos, Alibaba Cloud or Docker Compose. It centres on an Agent Builder, Agent Groups that work a task in parallel, Pages for co-writing, scheduled runs, projects and shared workspaces, plus structured editable memory and an IM gateway, with 10,000+ tools and MCP-compatible plugins. An OpenAI API key is required to start.
Who it is for: Teams wanting a multi-agent workspace with an app-like UI
Strengths
- One-click deploy buttons for Vercel, Zeabur, Sealos, RepoCloud and Alibaba Cloud
- 10,000+ tools and MCP-compatible plugins for agents
- Agent Groups, scheduled runs, projects and team workspaces
- Memory is structured and editable rather than a hidden store
Weaknesses
- OPENAI_API_KEY is a required environment variable
- Docker setup runs a curl-piped script from lobe.li before docker compose up
- README recommends a third-party API reseller through an affiliate link
- README states no ports, databases or hardware requirements
- no GPU
- Docker + Compose
- Models: OpenAI, OpenAI-compatible proxy
Onyx
Onyx indexes content and permissions from 50+ apps into a hybrid vector and keyword index, then answers through agentic RAG, deep research and custom agents with web search, MCP actions and a code sandbox. It works with Ollama, LiteLLM, vLLM, Anthropic, OpenAI or Gemini, deploys via Docker, Kubernetes or Helm, and is reachable from the web app, Slack and Discord bots, an MCP server or a Chrome extension.
Who it is for: Teams wanting an internal search and chat layer over company apps
Strengths
- Lite mode runs the chat UI and agents in under 1 GB of memory
- Air-gappable: index, database and processing all run inside your environment
- MCP server gives Claude Code, Codex or any MCP client company context with user permissions
- Community Edition is MIT; install script sets up Docker in one command
Weaknesses
- SSO (OIDC, SAML), SCIM, RBAC, analytics and whitelabeling are Enterprise Edition only
- Standard mode adds index, worker, inference, Redis and MinIO containers
- Lite mode cannot index documents
- README gives no port or hardware figures for the Standard deployment
- RAM ≥ 1 GB
- no GPU
- Compose
- Needs Redis (standard mode), MinIO (standard mode)
- Models: Ollama, LiteLLM, vLLM, Anthropic, OpenAI