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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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    Provides comprehensive BioPython capabilities for biological sequence analysis, alignment, database access (GenBank, UniProt, PubMed), protein structure analysis, and phylogenetics through a Model Context Protocol interface for AI-assisted bioinformatics workflows.
    32
    3
    MIT
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    A comprehensive Model Context Protocol (MCP) server for accessing the STRING protein interaction database. This server provides powerful tools for protein network analysis, functional enrichment, and comparative genomics through the STRING API.
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    A Model Context Protocol server that enhances language models with protein structure analysis capabilities, enabling detailed active site analysis and disease-related protein searches through established protein databases.
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    Enables querying and browsing ontologies from the EBI Ontology Lookup Service, including searching for terms, retrieving term details, and navigating ontology hierarchies via natural language.
    15
    MIT
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    Enables deep probabilistic analysis of single-cell omics data using scvi-tools through natural language. Supports SCVI for scRNA-seq analysis, SCANVI for cell type annotation, TOTALVI for multi-modal RNA/protein data, and PEAKVI for scATAC-seq analysis.
    MIT
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    Enables AI assistants to create, monitor, and manage computational tasks through GA4GH Task Execution Service (TES) functionality. Provides seamless access to TES-compliant services for executing bioinformatics and scientific computing workflows.
    Apache 2.0
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    A Model Context Protocol server providing programmatic access to 3D protein structural data from RCSB PDB, PDBe, and UniProt, enabling search, retrieval, comparison, and analysis of protein structures.
    269
    5
    Apache 2.0
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    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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    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
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    MCP server for RNA-seq downstream analysis, wrapping R scripts to generate plots and perform analyses like PCA, volcano, heatmap, enrichment, and WGCNA.
    MIT
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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.
    1
    MIT
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    Enables natural language interface for single-cell RNA-Seq analysis using Liana. Supports reading/writing scRNA-Seq data, cell-cell communication analysis, and visualization through circle plots and dotplots.
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    Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.
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