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    MCP server for interacting with Galaxy bioinformatics platform, enabling AI assistants to connect to Galaxy instances, search and execute tools, manage workflows, and access other features.
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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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    🔍 A biomedical literature annotation and relationship mining server based on PubTator3, providing convenient access through the MCP interface.
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    MIT
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    A specialized MCP server for Metal-Organic Framework research that provides tools for database searching, structural optimization, and energy calculations via ASE. It enables scientific workflows by allowing users to interact with MOF data and perform chemical simulations through a standard SSE interface.
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    MIT
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    Enables natural language interface for single-cell RNA-Seq analysis using Liana. Supports reading/writing scRNA-Seq data, cell-cell communication analysis, and visualization through circle plots and dotplots.
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    Provides a natural language interface for single-cell RNA-Seq analysis using the decoupleR framework. It enables users to perform biological pathway inference, data clustering, and visualization through MCP-compatible AI clients.
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    Control PyMOL from Cursor via natural language. Enables describing molecular structures and styles in plain language to execute PyMOL commands through XML-RPC.
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    🔍 Enable AI assistants to search and access bioRxiv papers through a simple MCP interface. The bioRxiv MCP Server provides a bridge between AI assistants and bioRxiv's preprint repository through the Model Context Protocol (MCP). It allows AI models to search for biology preprints and access their
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    Provides a natural language interface for inferring Copy Number Variations (CNVs) from scRNA-Seq data using the infercnvpy framework. It enables users to perform data preprocessing, CNV inference, and visualization through chromosome heatmaps, UMAP, and t-SNE plots.
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    Enables protein modeling and design using the Rosetta suite via Docker, including structure refinement, mutation stability analysis, docking, and loop modeling through natural language commands.
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