LobeHub: Your Chief Agent Operator for AI Team Orchestration
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
LobeHub acts as a Chief Agent Operator, streamlining the management of your AI team. It enables hiring, scheduling, and reporting on agents for 24/7 operations, allowing users to maintain control without constant online presence. This platform transforms individual AI tools into a cohesive, productive team.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
LobeHub is an innovative open-source project, built with TypeScript, that redefines how individuals and teams manage AI agents. Positioned as a "Chief Agent Operator," it provides a unified platform to organize, manage, and orchestrate your entire AI team, addressing the fragmentation common in current AI tools. By bringing agents under one roof, LobeHub fosters seamless collaboration and continuous operation, creating an environment where humans and AI agents co-evolve efficiently.
Installation
Getting started with LobeHub is designed to be straightforward, offering flexible deployment options.
For rapid cloud deployment, platforms like Vercel, Zeabur, Sealos, or Alibaba Cloud are supported. These typically require your OpenAI API Key and a simple one-click deployment process, as detailed in the official documentation.
For those preferring self-hosting and greater control, Docker provides a robust solution. Begin by creating a dedicated directory for storage:
mkdir lobehub-db && cd lobehub-db
Next, initialize the LobeHub infrastructure using the provided setup script:
bash <(curl -fsSL https://lobe.li/setup.sh)
Finally, launch the LobeHub service with Docker Compose:
docker compose up -d
It is crucial to configure your OPENAI_API_KEY as an environment variable for any chosen deployment method. Comprehensive instructions and a full list of environment variables are available in the official documentation.
Examples
LobeHub fundamentally transforms AI interaction through its powerful features:
- Operator: Agents as the Unit of Work: This core concept allows you to manage your entire AI team from a single interface. LobeHub handles the hiring, scheduling, and reporting of agent activities, maximizing productivity and minimizing tool switching.
- Create: Agent Builder: Building a personalized AI team begins with the Agent Builder. You can define your requirements, and the system automatically configures agents, providing unified access to various models and an extensive library of over 10,000 skills through MCP-compatible plugins.
- Collaborate: Agent Groups: LobeHub facilitates working with agents as true teammates. Agent Groups enable parallel collaboration and iterative improvements, supported by features like Pages for content refinement, Schedule for automated tasks, and Workspaces for organized team projects.
- Evolve: Co-evolution of Humans and Agents: The platform features "Personal Memory," allowing agents to learn from your work habits and adapt their behavior. This memory is structured and editable, ensuring transparency and giving you full control over your agents' learning and evolution.
Why Use LobeHub
LobeHub offers a compelling solution for anyone looking to streamline and enhance their AI workflows. By consolidating disparate AI tools into a single, intelligent platform, it significantly boosts productivity and fosters a more cohesive AI team environment. Its unique approach of treating "Agents as the unit of work" enables structured collaboration, continuous learning, and highly personalized AI experiences. With flexible self-hosting options, a vibrant community, and an expanding plugin ecosystem, LobeHub is a versatile and powerful tool for building and managing sophisticated AI operations that adapt and grow with your evolving needs.
Links
- GitHub Repository: https://github.com/lobehub/lobehub
- Official Site: https://lobehub.com
- Documentation: https://lobehub.com/docs/usage/start
- Discord Community: https://discord.gg/AYFPHvv2jT
Related repositories
Similar repositories that may be relevant next.

open-slide: An AI-Native Slide Framework for React Presentations
September 9, 2026
open-slide is a powerful slide framework built for AI agents, enabling users to create presentations by describing them in natural language. Coding agents then generate the React components, while open-slide handles the canvas, scaling, navigation, and presentation modes. This allows agents to focus entirely on content, streamlining the creation of polished, agent-driven decks.

best-skills: Daily-Updated Rankings for Top Agent Skills
September 8, 2026
The LinklyAI/best-skills repository offers daily-updated rankings of the top 100 agent skills. It aggregates data on installs, growth, and social buzz from various platforms like skills.sh, ClawHub, Tencent SkillHub, GitHub, and X. This open-data project provides a comprehensive, cross-ecosystem view of agent skill performance, making it an invaluable resource for developers and researchers.

Context Engineering Kit: Enhance AI Agent Quality with Advanced Skills
September 6, 2026
The Context Engineering Kit is a powerful collection of hand-crafted Claude Code Skills designed to significantly improve the quality and predictability of AI agent results. It offers advanced context engineering techniques with a minimal token footprint, ensuring efficiency and effectiveness across platforms like OpenCode, Cursor, and Gemini CLI. This kit provides granular control over plugins and includes an open-source alternative to CodeRabbit, enhancing development workflows.

Agent Factory: Generate AI Agents with Natural Language Descriptions
September 3, 2026
Agent Factory, developed by Mozilla-AI, is a powerful tool designed to generate AI agents and workflows. It allows users to describe tasks in natural language, which it then transforms into executable Python code for agentic workflows. Leveraging the Model Context Protocol (MCP) and the any-agent library, it simplifies the creation of complex AI solutions.
Source repository
Open the original repository on GitHub.
17 counted GitHub visits