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    Provides a collection of MCP servers for computational chemistry tasks including molecular generation and retrosynthesis. Also offers property prediction and molecule pricing capabilities.
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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
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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.
    MIT
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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
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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.
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    Apache 2.0
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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.
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    MIT
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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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    MIT
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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.
    37
    MIT
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    MCP-native scientific skills for reproducible computational biology and AI-driven drug-discovery workflows. It combines deterministic scientific tools with an MCP server to give AI agents real computational capabilities.
    Apache 2.0
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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.
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    Enables LLMs and AI agents to query a biomedical knowledge graph stored in RedisGraph, with tools for concept search, synonym enrichment, and study variable discovery through semantic relationships.
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    Manages local protein experiments with a Flask backend and SQLite, offering tools for protein library management, Beer-Lambert concentration calculations, BLI dilution planning, and experiment archiving. It provides 7 MCP tools for AI assistants like Claude to interact with the system.