We decode nature's molecular language using generative AI to discover breakthrough therapeutics, learning from millions of years of evolution.
Our platform combines computational biology with machine learning to identify novel drug targets and accelerate pharmaceutical research.
In parallel, we contribute to the open-source community by developing Model Context Protocol (MCP) Servers that make key biological, chemical, and genomic datasets more accessible to researchers worldwide.
- Therapeutics Platform: Harnessing generative AI and computational biology to uncover novel drug targets and speed up drug discovery.
- Open-Source MCP Servers: Providing standardized APIs for major life sciences datasets, enabling seamless data integration and exploration.
Some of our active repositories:
| Repository | Summary |
|---|---|
| OpenFDA-MCP-Server | MCP server for the OpenFDA dataset (drug and device regulatory info in the US). |
| OpenGenes-MCP-Server | Enables querying of “Open Genes” data with the Model Context Protocol. |
| ClinicalTrials-MCP-Server | Access to clinical trials information exposed via MCP. |
| BioThings-MCP-Server | MCP interface to curated biological data (various sources). |
| NCBI-Datasets-MCP-Server | Access to NCBI Datasets API; search and retrieve genomic, taxa, etc. |
| SureChEMBL-MCP-Server | Chemical patent database from SureChEMBL via MCP. |
| KEGG-MCP-Server | Pathways, genes, compounds, etc. via KEGG database. |
| UniProt-MCP-Server | Representation of the UniProt protein database via MCP. |
| ChEMBL-MCP-Server | Chemical bioactivity data via ChEMBL exposed by MCP. |
| AlphaFold-MCP-Server | Protein structure predictions and associated metadata from AlphaFold. |
| PDB-MCP-Server | Protein Data Bank structures and related data. |
| STRING-db-MCP-Server | Protein interaction networks via STRING database. |
| PubChem-MCP-Server | Compounds, properties, bioassays etc from PubChem. |
| OpenTargets-MCP-Server | Gene-drug-disease association data from Open Targets. |
| Reactome-MCP-Server | Pathways and systems biology content via Reactome. |
| Ensembl-MCP-Server | Genomic annotations, comparative genomics, etc via Ensembl. |
| GeneOntology-MCP-Server | Ontology and annotation info via Gene Ontology. |
| ProteinAtlas-MCP-Server | Expression and spatial proteomics via Protein Atlas. |
| BioOntology-MCP-Server | Various biomedical ontologies accessible via MCP. |
- AI for therapeutics: We aim to shorten the path from idea to medicine.
- Unified data access: Our MCP servers provide standardized access to dozens of datasets.
- Open collaboration: By contributing to the open-source community, we empower researchers everywhere.
To use any of our MCP servers:
- Pick the MCP server for the dataset you need (for example,
UniProt-MCP-Server). - Review its README in that repo for usage instructions.
- Query the endpoints using REST or an MCP-compatible client.
- Combine datasets for richer workflows (e.g. UniProt + STRING + Reactome).
We welcome collaboration across both our therapeutics mission and our open-source MCP projects:
- Open issues or feature requests in our repositories.
- Submit pull requests to improve code or docs.
- Contribute examples, tutorials, or integrations.
- Suggest new datasets you’d like to see supported.
For questions, feedback, or partnership inquiries:
- Open an issue in the relevant repository
- Or reach us at [moudather.chelbi@gmail.com]
💡 At Augmented Nature, we believe evolution has already written the greatest library of molecular solutions.
Our mission is to read it, learn from it, and translate it into tomorrow’s medicines.