OpenMAIC GitHub Project: Open-Source Multi-Agent AI Classroom
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OpenMAIC (Open Multi-Agent Interactive Classroom) is an open-source AI education platform that transforms topics or learning materials into interactive classroom experiences. It uses multi-agent orchestration to create lessons, slides, quizzes, simulations and project-based learning activities, while AI teachers and AI classmates can interact with learners through discussions, voice and whiteboard-based explanations.
What Is OpenMAIC?
OpenMAIC aims to move AI-assisted learning beyond simple chatbot conversations.
A learner can provide a topic or upload learning materials, and the platform can generate a structured classroom containing different types of educational content. Its classroom experience can include AI teachers, AI peers, interactive activities, quizzes and discussions.
The project is developed by the THU-MAIC team and is available as an open-source GitHub project.
Key Features
One-Click Lesson Generation
Users can describe what they want to learn or provide reference materials. OpenMAIC can then generate a complete lesson containing structured scenes and learning activities.
Supported material types include documents, audio, video and other learning resources.
Multi-Agent Classroom
Instead of relying on a single AI assistant, OpenMAIC creates a classroom environment with multiple AI participants.
These can include:
- AI teachers
- AI classmates
- Discussion agents
- Q&A agents
- Role-based participants
Agents can participate in classroom discussions and respond to learner interaction.
Interactive Learning
OpenMAIC supports several interactive classroom formats, including:
- Slides
- Quizzes
- Interactive HTML simulations
- Project-Based Learning (PBL)
- 3D visualizations
- Games
- Mind maps
- Online programming activities
The Deep Interactive Mode is designed around hands-on exploration rather than passive content consumption.
AI Whiteboard
AI agents can use a shared whiteboard to explain concepts visually.
For example, an AI teacher can:
- Draw diagrams
- Write formulas
- Create flowcharts
- Explain concepts step by step
- Display runnable code
This makes the classroom experience more interactive than conventional text-based AI tutoring.
Agent Workbench
One of the major additions in OpenMAIC v1.0.0 is the Agent Workbench.
Released on August 27, 2026, it provides a chat-based workspace where an agent can plan a curriculum, create courses, build pages and revise generated content. Sessions are server-backed, allowing users to resume or steer ongoing work.
The workbench can also work with uploaded materials and web-sourced information.
Course Export
OpenMAIC allows generated educational content to be exported in different formats.
PowerPoint
Courses can be exported as editable .pptx presentations containing elements such as images, charts and LaTeX formulas.
Interactive HTML
Interactive lessons can also be exported as self-contained HTML pages, allowing simulations and interactive content to be shared.
Classroom ZIP
Complete classroom projects can be exported as .maic.zip packages for backup or sharing.
AI Model & Provider Flexibility
OpenMAIC is designed to be relatively provider-neutral.
The current project supports configurable AI providers including options such as:
- OpenAI
- Anthropic
- Grok
- OpenRouter
- Azure OpenAI
- Tencent
The exact available providers and models can change with project releases and configuration.
OpenClaw & Agent Integration
OpenMAIC also provides an OpenMAIC Skill that can be used with agent workbenches including OpenClaw, Codex, DeepSeek and WorkBuddy.
With supported integrations, users can generate classrooms through messaging platforms or directly from their development environment.
Technology Stack
The repository is primarily built around modern web technologies and a modular package architecture.
Key technologies include:
- TypeScript
- React
- Next.js
- Tailwind CSS
- Node.js
- PostgreSQL
- Electron-related integrations
- AI/LLM provider APIs
- Interactive HTML/Web technologies
The repository's current package configuration specifies Node.js 22.19+ and uses Next.js development/build scripts.
What Developers Can Learn
OpenMAIC is particularly useful for developers interested in:
- Multi-agent AI systems
- AI education platforms
- LLM orchestration
- Interactive UI generation
- AI-powered content generation
- React and TypeScript
- Next.js application architecture
- Document processing
- Text-to-speech systems
- Interactive simulations
- AI agents and tool calling
- Export pipelines
- Internationalization
Its architecture provides a practical example of combining LLMs, agents, interactive interfaces and educational workflows into a single application.
Getting Started
The official repository currently lists Node.js >= 22.19 and pnpm >= 10 as prerequisites.
Basic setup:
git clone https://github.com/THU-MAIC/OpenMAIC.git
cd OpenMAIC
pnpm install
cp .env.example .env.local
You then configure at least one supported LLM provider and start the development environment according to the repository instructions.
Open-Source License
OpenMAIC is currently released under the MIT License. The repository also notes that certain bundled third-party packages have their own licenses, so developers should review those terms when redistributing the project.
Why Developers Should Explore OpenMAIC
OpenMAIC demonstrates how AI can be used to build an entire interactive learning environment, rather than simply generating answers in a chat window.
Its combination of multi-agent orchestration, interactive course generation, AI teachers, simulations, project-based learning, whiteboards, voice interaction and agent workbench capabilities makes it a substantial open-source project for developers exploring the future of AI-powered education.
Official Resources
GitHub Repository: https://github.com/THU-MAIC/OpenMAIC
Live Platform: https://open.maic.chat
License: MIT
Final Thoughts
OpenMAIC represents an interesting direction for AI-powered education: from asking an AI a question to actually learning inside an AI-generated classroom.
For students, educators and developers, the project provides an example of how LLMs, multi-agent systems and interactive software can work together to create richer learning experiences.
