Enables first-principles calculations (SCF, structure optimization, molecular dynamics, etc.) for quantum chemistry and materials science using ABACUS, with intelligent parameter suggestions and result analysis through natural language.
Enables natural language interaction with computational chemistry tools including molecule building, electronic structure calculations, geometry optimization, vibrational spectroscopy, and molecular dynamics, powered by RDKit, PySCF, and ASE.
Enables LLM agents to run verified DFT materials workflows (structure fetch, relaxation, band/DOS) with automated convergence gates and physics validation, ensuring every result is machine-verified with a complete evidence trail.
An MCP server for quantum chemistry that enables LLMs to perform electronic structure analysis, parse calculation outputs, and generate 3D orbital visualizations. It integrates tools like PySCF, cclib, and py3Dmol to facilitate molecular structure manipulation and bonding analysis through natural language.
A tool for querying and analyzing materials data from the Materials Project database using natural language prompts, enabling materials scientists to explore properties, structures, and compositions of materials through conversational interfaces.
Enables AI assistants to execute computational chemistry and drug discovery workflows using Schrödinger Suites 2026, including protein preparation, docking, ADMET, QM/MM calculations, and job management.
