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    Enables AI assistants to perform quality control analysis on high-throughput sequencing data using FastQC and MultiQC. It supports single-file and batch processing of FASTQ/FASTA files and generates comprehensive, interactive summary reports.
    MIT
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    Enables querying and retrieving bacterial and viral genomic data, features, antimicrobial resistance, and epitopes from the BV-BRC API using natural language.
    MIT
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    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.
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    BSD 3-Clause
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    A professional MCP server for comprehensive bioinformatics quality control, providing automated FastQC/MultiQC analysis, HTML report parsing, and advanced data visualization for sequencing data.
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    MIT
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    Provides a natural language interface for inferring Copy Number Variations (CNVs) from scRNA-Seq data using the infercnvpy framework. It enables users to perform data preprocessing, CNV inference, and visualization through chromosome heatmaps, UMAP, and t-SNE plots.
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    Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.
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    A Model Context Protocol server that interfaces with Biomart databases, allowing models to discover biological datasets, explore attributes/filters, retrieve biological data, and translate between different biological identifiers.
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    MIT
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    An MCP server that gives Claude access to NCBI Datasets v2 — search genome assembly metadata, retrieve taxonomy records, and download data packages without leaving your conversation.
    10
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    Provides a Model Context Protocol server for accessing and querying biomedical data from BioThings services, including gene, variant, chemical, and taxon annotations.
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    MIT
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    Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.
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    MIT