Enables molecular visualization and analysis from SMILES strings using multiple rendering approaches (RDKit, NetworkX, Plotly, matplotlib), providing detailed molecular properties, validation, and batch processing capabilities for chemical structures.
Enables generation of chemical structures, reactions, spectra, titration curves, 3D models, and more from natural language or SMILES, using RDKit for offline rendering and supporting formats like PNG, SVG, CDXML, and Anki decks.
Enables AI assistants to deterministically render accurate 2D organic chemistry structures, reactions, mechanisms, resonance contributors, and stereochemistry directly in chat, with curated JEE presets and fallback resolution.
Provides an MCP interface for publication-quality chemical structure and reaction rendering from SMILES/InChI/molblock, with validation and name parsing. Enables AI agents to draw molecules and reactions as images.
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 AI assistants to search and retrieve chemical compound information, structures, and physical properties from the PubChem database. It supports querying via compound names, SMILES notation, or CIDs to provide detailed molecular data for chemical analysis.
