Huagongshe: open chemical data, professional chemistry tools, and an AI chemistry workbench
Chemical research and production rely on data. From looking up the structure and properties of a compound, to finding relevant reactions, analyzing synthesis routes, and calculating experimental quantities, accurate data and capable tools directly affect how efficiently the work gets done.
As artificial intelligence moves into chemical research and industrial applications, the way chemical data is used is changing as well. Researchers want more convenient access to information, developers need professional capabilities they can call directly, and AI agents need reliable tools that can understand and process chemical structures.
HGS AIchem (Huagongshe) is built around these needs, providing an open platform for chemical data and tools where chemical information can be queried, linked, computed, and fed directly into AI workflows.
Starting from compounds, connecting chemical data
Chemical information carries a complex system of identifiers. The same substance may have multiple names, registry numbers, and structural representations, and data from different sources may contain duplicates, ambiguities, or conflicts.
Building on compounds and chemical reactions, Huagongshe continuously integrates publicly available chemical data, and improves the retrievability and usability of chemical information through chemical structure standardization, entity recognition, and data linking.
According to data previously released by the platform, HGS has collected more than 120 million compound records and 2.4 million chemical reaction records.
Users can search by compound name, CAS Registry Number, SMILES, or InChIKey, and can also use exact-structure, substructure, and similarity searches to find target compounds from different entry points.
Around each chemical entity, the platform further links molecular structures, identifiers, basic information, and related reactions, so that a single query becomes the starting point for further analysis and research.
Data scale provides coverage, while data governance determines usability. HGS continuously handles identity matching, duplicate records, and identifier conflicts across sources, preserving the necessary links and provenance information to reduce the impact of incorrect merges on downstream use.
Putting professional chemistry tools to work
Chemistry needs more than information; it also needs the ability to process it.
HGS AIchem integrates commonly used cheminformatics capabilities into the platform, supporting molecular structure search, structure drawing and rendering, reaction information queries, stoichiometry, and experimental quantity calculations.
For example, when preparing a synthesis experiment, a user can look up the target compound and related reactions, view the corresponding molecular structures, and then calculate reagent amounts and theoretical yields according to the established stoichiometry and the scale of the experiment.
These operations revolve around compounds and reactions, so that data queries and professional calculations form one continuous working process.
For researchers, this is an everyday research aid; for chemical information users, a unified entry point for obtaining and processing professional data; for application developers, capabilities that can be further integrated through standard interfaces.
From finding data to using data, HGS makes professional chemistry capabilities easier to obtain.
Letting AI call chemical data and tools directly
Applying AI in chemistry requires the support of professional data and executable tools.
General-purpose language models can understand natural language, organize information, and analyze problems, but when it comes to chemical entity recognition, molecular structure processing, reaction data queries, and precise stoichiometric calculations, they need to call dedicated chemical data services and computational tools.
HGS AIchem opens up its chemistry capabilities through MCP (Model Context Protocol), allowing AI clients and agents that support the protocol to connect to Huagongshe directly.
The platform currently provides 13 MCP tools, covering chemical data retrieval, compound and reaction queries, structure rendering, stoichiometric calculations, personal reaction records, and professional Skills.
For example, when a user asks an AI client to "look up the structure and related reactions of a compound, and calculate reagent quantities at a specified scale," the agent can call HGS data and tools as the task requires, obtain structured results, and organize them into content that is easy to read and use.
Public query capabilities are available without login, while features involving personal data, specific structure searches, and save operations are managed through account authorization.
The platform also offers an Agent Plugin access method, helping compatible agent clients discover and use the professional capabilities of HGS.
For developers, this means ready-made chemical data and tool interfaces that reduce duplicated infrastructure work; for everyday users, it means completing more professional chemistry tasks within a familiar AI working environment.
From a single query to a continuously growing chemistry workbench
Chemical research often involves large amounts of scattered information: compounds looked up, reactions referenced, calculation results, and experiment records.
HGS AIchem provides a personal chemistry workbench that supports bookmarking chemical data, managing reaction records, and organizing related information around chemical entities.
Users can save their own reaction data, recording reactants, products, conditions, and yields, and control the visibility of each record.
With authorization, AI can also help query, verify, and organize reaction drafts, which are saved only after the user confirms them.
The platform also supports the organization and reuse of professional task methods through a Skills mechanism, helping AI use tools in a more consistent way in specific chemistry scenarios.
In this way, chemical data no longer stops at one-off lookups, but continues to serve personal research, reference organization, and future work.
Opening up chemistry capabilities, connecting more applications
The value of chemical data is ultimately reflected in how much real work it can support.
For researchers, HGS provides chemical entities, reaction information, and computational tools; for practitioners in the chemical, pharmaceutical, and materials industries, a unified entry point for chemical information queries; for developers and AI agents, professional capabilities that can be connected and called.
As its data system and tooling continue to improve, HGS AIchem aims to turn more chemical information from scattered references into reusable digital resources, and to help professional tools fit into different research environments and application scenarios.
Making chemical data easier to obtain, professional tools easier to use, and AI a better participant in chemical work.
That is the direction HGS AIchem keeps building toward.
About HGS AIchem (Huagongshe)
HGS AIchem (Huagongshe) is an open AI chemistry workbench for chemical research and industrial applications. Built on compound and chemical reaction data, it provides chemical information retrieval, molecular structure processing, professional calculations, personal research records, and AI agent integration.
The platform can be used directly on the web, and opens its professional chemistry tools to compatible AI clients through MCP and the Agent Plugin.
Official website: https://huagongshe.com
MCP access: https://huagongshe.com/mcp
Getting started guide: https://huagongshe.com/mcp-guide
HGS AIchem | Chemical Data · Professional Tools · AI Chemistry Workbench