MoziChem Hub
Provides a modular Python toolkit for creating Model Context Protocol (MCP) modules specifically designed for chemical engineering and chemistry workflows.
About
MoziChem Hub is a powerful and modular Python toolkit engineered to bridge the gap between traditional computational chemistry and process modeling tools and modern AI workflows. It enables researchers, engineers, and developers to easily expose their domain-specific computational tools as standardized MCP servers, making them accessible via robust REST APIs. By integrating with existing and emerging AI agents and large language models, MoziChem Hub ensures that these intelligent systems can access reliable, validated results crucial for complex chemical and engineering problems, transforming workflows with scalable and trustworthy applications.
Key Features
- Support for custom references and integration with external thermodynamic databases like PyThermoDB
- Pre-built MCP modules for advanced thermodynamic property calculations (EOS models), comprehensive flash calculations, and robust thermodynamic data lookup
- Build custom Model Context Protocol (MCP) modules for chemical engineering and chemistry calculations
- 1 GitHub stars
- Deploy MCP modules instantly as REST APIs using FastAPI for production environments
- Integrate universally with any client ecosystem, including cloud platforms, IDEs, and custom GUIs
Use Cases
- Integrating domain-specific computational chemistry and process modeling tools with AI workflows and LLMs
- Exposing chemical engineering calculation capabilities as standardized APIs for seamless client ecosystem integration
- Developing custom MCP servers for bespoke thermodynamic and chemical property calculations
