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"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

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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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    8
    MIT
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    Provides a Model Context Protocol server for accessing and querying biomedical data from BioThings services, including gene, variant, chemical, and taxon annotations.
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    MIT
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    Provides LLMs with structured access to critical biomedical databases including PubTator3 (PubMed/PMC), ClinicalTrials.gov, and MyVariant.info through the Model Context Protocol.
    35
    591
    MIT
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    A Model Context Protocol server providing LLMs with access to the Ensembl genomics database, enabling AI assistants to query gene information, sequences, variants, and other genomic data across multiple species.
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    JavaScript
    MIT
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    A framework that integrates Brain-Computer Interface technology with the Model Context Protocol to enable real-time neural signal processing and AI-powered interactions for healthcare, accessibility, and research applications.
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    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 provides tools for interacting with the STRING database to analyze protein-protein interaction networks and functional enrichment. It enables users to map protein identifiers, retrieve interaction data, and generate biological network visualizations through natural language interfaces.
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    BSD 3-Clause
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    Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.
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    2
    MIT
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    Enables running GROMACS molecular dynamics simulations through natural language, with tools for topology building, solvation, simulation management, and trajectory processing via the Model Context Protocol.
    31
    MIT
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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.
    2
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    A Model Context Protocol server that lets you drive PyMOL with natural language, enabling structure loading, analytical views, measurements, and protein exploration through AI assistants.
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    15
    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.
    2
    BSD 3-Clause
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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