PubChem
Enables querying of the PubChem database for chemical compound data and generating structure files.
About
PubChem provides a Model Context Protocol (MCP) server, implemented in Python, that enables AI models to easily retrieve chemical compound information from the PubChem database. Through a standard MCP interface, users can access compound properties, 2D structures, and 3D molecular coordinates, enhancing the capabilities of AI in chemical and scientific applications.
Key Features
- Queries compounds by name or PubChem CID
- Supports JSON, CSV, and XYZ output formats
- Retrieves comprehensive compound data including IUPAC name, molecular formula, and SMILES notation
- Includes a built-in caching system for improved performance
- Offers automatic retry mechanism for API reliability
- 3 GitHub stars
Use Cases
- Retrieving chemical compound data for AI model training
- Integrating chemical data into AI-driven scientific workflows
- Generating structure files for visualization and analysis
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