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    A bridge connecting AI agents to NCBI's PubMed database through the Model Context Protocol, enabling seamless searching, retrieval, and analysis of biomedical literature and data.
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    Apache 2.0
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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 AI assistants to perform NCBI BLAST sequence similarity searches through natural language, supporting nucleotide and protein searches, custom database creation, and multiple output formats.
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    MIT
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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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    An MCP server that enables AI assistants to generate, score, and analyze DNA sequences using the evo2 genomic foundation model. It supports multiple execution modes including local GPU, SLURM clusters, and the Nvidia NIM cloud API for tasks like variant effect prediction and sequence embedding.
    MIT
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    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.
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    MIT
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    Enables AI assistants to perform DNA/RNA sequence alignment using BWA (Burrows-Wheeler Aligner), supporting both short and long read alignment to reference genomes with indexing, BWA-MEM, and BWA-backtrack algorithms.
    MIT
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    This server provides access to InterPro protein family, domain, and functional-site classification data from EBI. It allows querying protein annotations through natural language or direct tool calls.
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    MIT
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    Federates 13 gene-related MCP backends (gnomAD, GTEx, etc.) behind a single Streamable HTTP endpoint with collision-free namespacing and search-based tool discovery.
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    MIT
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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.
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    Apache 2.0
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    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