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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 MCP-capable AI clients to characterize proteins end to end: PDB/mmCIF validation, sequence extraction and typing, pLDDT confidence summaries, metal-site geometry with bidentate chelate detection, GROMACS trajectory metrics and plots, and live UniProt, AlphaFold DB, and RCSB lookups. Also ships a point-and-click Protein Lab web UI (and a persistent run registry) so students and wet-lab biologists can get the same results without any client setup.
    31
    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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    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 LLM-powered applications to look up bacterial and archaeal taxonomy, search genomes, browse and navigate the taxonomic tree, and compare genomes or find phylogenetic paths between taxa. It works out of the box with a built-in reference dataset covering major phyla and can be pointed at full Genome Taxonomy Database TSV files for comprehensive queries.
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    MIT
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    An MCP server that enables AI assistants to generate, score, and analyze DNA sequences using the evo2 genomic foundation model. It supports multiple execution modes including local GPU, SLURM clusters, and the Nvidia NIM cloud API for tasks like variant effect prediction and sequence embedding.
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    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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    Enables in-chat scientific viewers for molecular structures, sequence alignments, and slide images, plus data tools for searching structures, fetching sequences, aligning them, and drafting NGS analysis plans.
    ISC
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    A unified biomedical graph database that integrates 50+ primary data sources — genes, proteins, compounds, diseases, pathways, and clinical data — into a single queryable graph with billions of cross-reference edges. Its native MCP server gives LLMs direct access to structured, authoritative biomedical data, complementing their reasoning with reliable identifiers and up-to-date database content.
    20
    AGPL 3.0
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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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    Enables protein sequence analysis and structure prediction by extracting ESM-2 embeddings and batch processing FASTA files via Docker. It provides tools for large-scale embedding extraction, job monitoring, and model management within an MCP-compatible environment.
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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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    Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.
    11
    MIT
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    Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.
    9
    MIT