An agentic AI platform for computational materials science.
Build workflows, generate structures, run simulations, and continuously acquire new skills.
Documentation · Quick Start · Launch
- 🧠 Agentic workflow planning using graph-based execution
- 🔬 Materials science focused, from crystal generation to MLFF workflows
- 🧩 Skill-based architecture — capabilities are modular and extensible
- 📚 Self-improving knowledge graph that accumulates experience over time
- 🌐 Modern Web UI with graph visualization and artifact management
- ⚡ CLI + API + Web interfaces
git clone https://github.com/AI4MS/MatCreator.git
cd MatCreator
pip install uv
uv venv .venv --python 3.12
source .venv/bin/activate
uv pip install -e .Configure your LLM credentials through the MatCreator CLI
matcreator config set llm.model=openai/qwen3-plus
matcreator config set llm.api_key=your-api-key
matcreator config set llm.base_url=https://api.example.com/v1Start an interactive session from the workspace you want MatCreator to use
matcreator chat --workspace .MatCreator can install corporation-maintained official skills from the SkillForge repository managed by the MatCreator team.
These skills are installed into ~/.matcreator/skills/official and loaded alongside built-in and custom skills.
Notice: Only authenticated users with repository access can install official skills from SkillForge.
matcreator install official --repo [email protected]:AI4MS/SkillForge.git --ref develIf your repository requires authentication, configure your Git SSH keys or credential helper first.
The Vite frontend uses Ketcher and requires Node.js 24.14.1 or later. Install the frontend dependencies with:
cd web/vite-frontend
npm installCheck the installed versions with:
node --version
npx vite --versionbash script/start_matcreator.shThis starts
- ADK API
- FastAPI backend
- Vite frontend
matcreator chat
matcreator chat --workspace ~/materials-projectBy default, matcreator chat starts in Flash mode for fast direct interaction. Use matcreator chat --plan when you want the full planning and graph-execution workflow.
Full installation, configuration, and deployment documentation is available at ai4ms.github.io/MatCreator.
MatCreator aims to become a continually evolving AI scientist for computational materials research by combining
- Large language models
- Scientific software
- Modular skills
- Long-term knowledge accumulation
into a unified agentic system.
Apache 2.0
