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"Allowing an AI agent to ask user questions during a task" matching MCP servers:

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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.
    6
    1
    MIT
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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 for searching and accessing RNA sequencing datasets from the European Nucleotide Archive (ENA), supporting bulk, single-cell, and spatial transcriptomics with advanced filtering and download capabilities.
    11
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    Apache 2.0
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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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    11
    MIT
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    Enables LLM agents to query the CZ CELLxGENE Census single-cell atlas with ontology-aware filters, cost caps, and full provenance, allowing natural language questions about cell types, tissues, and gene expression.
    13
    MIT
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    A server that enables AI assistants to interact with cancer genomics data from cBioPortal, allowing users to explore cancer studies, access genomic data, and retrieve mutations and clinical information.
    17
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    MIT
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    Exposes pipen bioinformatics pipelines as MCP tools, allowing AI assistants to discover and run complex workflows through a progressive disclosure interface.
    1
    MIT
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    MCP server for querying gene annotations, full-text gene search, and species taxonomy via MyGene.info. Enables AI agents to access gene data through natural language questions.
    14
    MIT
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    MCP server that exposes STRING database functionality, allowing AI agents to resolve protein identifiers, retrieve interaction networks, perform homology lookups, and run functional enrichment analysis.
    5
    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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    Connects PyMOL to Claude AI through the Model Context Protocol, allowing for conversational structural biology and molecular visualization through natural language commands.
    67
    MIT
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    MCP server for gene family analysis, providing tools for FASTA validation and PlantCARE cis-element prediction, with backend task management for AI agents.