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"Using Gemini CLI for research purposes" matching MCP servers:

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    Enables the generation, mutation, and evolution of DNA and protein sequences using various evolutionary models and phylogenetic algorithms. It supports realistic next-generation sequencing read simulation and population-level evolutionary tracking for bioinformatics research and testing.
    6
    BSD 2-Clause "Simplified"
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    Provides AI-powered access to major biological databases for GWAS and bioinformatics research. Enables natural language queries for protein, gene, variant, pathway, and drug discovery analysis.
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    MIT
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    A terminal-based bioinformatics CLI chat tool that integrates Ensembl VEP, NCBI ClinVar, an MCP server layer, and OpenRouter's NVIDIA Nemotron 3 Ultra model to provide variant consequence and clinical significance lookups with clear summaries in a Rich-powered CLI.
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    An advanced integrated MCP server platform that combines 600+ tools and multiple biomedical databases to enable comprehensive information retrieval across molecules, proteins, genes, and diseases for accelerating therapeutic research.
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    An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.
    15
    MIT
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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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    3,327
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    Apache 2.0
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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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    Enables AI assistants to query the Ubergraph biomedical ontology SPARQL endpoint with tools for custom SPARQL queries, term lookup, search, and hierarchy traversal.
    4
    MIT
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    Enables gene set enrichment analysis using the Enrichr API across hundreds of gene set libraries including Gene Ontology, pathways, diseases, tissues, drugs, and transcription factors. Returns only statistically significant results for interpretation.
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    MIT
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    Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.
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    MIT