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ChemMCP

What is ChemMCP?

ChemMCP is a continuously updated collection of chemistry tools for LLMs and AI assistants, compatible with the Model Context Protocol (MCP). ChemMCP provides:

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Professional Chemistry Tools

ChemMCP equips you and your AI assistants with advanced tools to predict molecules and reactions, analyze chemical data, and explore scientific knowledge. Discover the full range in our tool directory.

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Effortless Integration with MCP

Easily supercharge your LLM clientsā€”such as Claude, GPT, and moreā€”using ChemMCP. With MCP, integrating powerful chemistry tools into your workflow takes just minutes via a simple JSON configuration.

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Seamless Support for Python

ChemMCP is also available as a Python package, enabling seamless integration into your projects for data analysis, agent development, or custom applicationsā€”ideal for researchers, developers, and innovators.

Where to Start?

Follow the steps below to embrace ChemMCP:

1. Read Get Started : Learn the fundamentals of using ChemMCP through our comprehensive guide.
2. Explore Tools : Browse our extensive collection of chemistry tools and their detailed documentation.
3. Configure with QuickConfig : Easily customize your tool selection and configuration with our easy-to-use utility.
4. Contribute to ChemMCP : Join our community by implementing new tools following our development guide, or help improve ChemMCP by reporting issues and suggesting features on GitHub .

About Us

ChemMCP is an open-source project developed by the OSU NLP Group and led by Botao Yu. We're pioneering the integration of advanced chemistry tools with large language models, bridging the gap between computational chemistry and AI. Our vision is to democratize access to sophisticated chemistry tools, empowering researchers and practitioners to tackle complex scientific challenges with the assistance of AI technology.

Citations

If ChemMCP is valuable to your research or development, please kindly cite our works:

@misc{yu2025chemmcp,
  author       = {Botao Yu and Huan Sun},
  title        = {ChemMCP: A Chemistry MCP Toolkit},
  year         = {2025},
  url          = {https://github.com/OSU-NLP-Group/ChemMCP},
}

@article{yu2024chemtoolagent,
  title={ChemToolAgent: The Impact of Tools on Language Agents for Chemistry Problem Solving},
  author={Botao Yu and Frazier N. Baker and Ziru Chen and Garrett Herb and Boyu Gou and Daniel Adu-Ampratwum and Xia Ning and Huan Sun},
  journal={arXiv preprint arXiv:2411.07228},
  year={2024}
}