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    MCP server offering verified bioinformatics tools for sequence utilities and statistics, backed by BioPython/scipy. Enables AI agents to perform accurate GC content, translation, ORF finding, motif scanning, and statistical tests through natural language.
    11
    MIT
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    quality
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    Enables searching and downloading Gene Expression Omnibus (GEO) data from NCBI, including datasets, series, samples, platforms, and profiles, through natural language queries.
    11
    12
    BSD 3-Clause
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    maintenance
    MCP server for querying the GWAS Catalog (EBI/NHGRI), a curated catalog of genome-wide association studies. It enables AI agents to search and retrieve study data via natural language or direct tool calls.
    7
    MIT
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    Annotate variants by with a deep and rich set of data. Can annotate: genetic change, rsID, CAid, HGVS (g./c./p.), protein change.
    5
    -
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    maintenance
    Federates 13 gene-related MCP backends (gnomAD, GTEx, etc.) behind a single Streamable HTTP endpoint with collision-free namespacing and search-based tool discovery.
    4
    MIT
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    maintenance
    Enables looking up genes, fetching sequences, predicting variant consequences, finding orthologs, and cross-database xrefs via Ensembl REST API through MCP.
    140
    2
    Apache 2.0
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    quality
    D
    maintenance
    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
    Apache 2.0
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    A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.
    MIT
  • A
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    quality
    C
    maintenance
    An MCP server that enables scRNA-Seq analysis through natural language, providing tools for data preprocessing, clustering, and biological visualization. It supports both predefined function execution and a flexible code mode powered by a Jupyter backend for automated single-cell transcriptomics workflows.
    16
    BSD 3-Clause