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    Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.
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    MIT
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    MCP server that provides tools for querying the Human Phenotype Ontology (HPO) including term lookup, hierarchy exploration, cross-ontology mappings, and gene-phenotype-disease associations, all grounded in a local SQLite database for fast offline lookups.
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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
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    Enables searching, retrieving, and downloading protein structure data from the RCSB Protein Data Bank. Supports intelligent protein structure search, comprehensive data retrieval, and multiple file format downloads for bioinformatics research.
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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.
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    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.
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    MIT
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    Enables AI coding agents to search academic papers, resolve biomedical entities, mine relations, and traverse citation graphs using Semantic Scholar and PubTator3, with local caching for reproducibility.
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    MIT
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    Enables AI assistants to query gene annotations, expression, pathways, variants, and more via the MyGene.info API, supporting batch operations and multiple biological data sources.
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    MIT
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    Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.
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    BSD 3-Clause
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    Enables quantum machine learning operations using Qiskit, including executing quantum circuits, computing quantum kernels, training variational quantum classifiers, and evaluating quantum ML models.
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    MIT
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    Enables Claude Code to interact with a TACC or SLURM HPC cluster for bioinformatics pipelines, allowing job management, log reading, file browsing, remote script execution, and job submission through natural language.
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