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"Improving the Intelligence of Large Language Models" matching MCP servers:

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    Enables editing and querying of Gene Ontology Causal Activity Models (GO-CAMs) through the Barista API. Supports model creation, individual and fact management, evidence addition, and causal pathway construction for biological knowledge representation.
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    BSD 3-Clause
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    Converts natural language queries into Cypher queries against the NASA GeneLab Knowledge Graph, enabling AI-assisted analysis of spaceflight experiments and their biological effects.
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    Enables the generation, mutation, and evolution of DNA and protein sequences using various evolutionary models and phylogenetic algorithms. It supports realistic next-generation sequencing read simulation and population-level evolutionary tracking for bioinformatics research and testing.
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    BSD 2-Clause "Simplified"
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    Leverages large language models to analyze users' WeGene genetic testing reports, providing access to report data via custom URI schemes and enabling profile and report management through OAuth authentication and API utilization.
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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.
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    MCP server for querying the GWAS Catalog (EBI/NHGRI), a curated catalog of genome-wide association studies. It enables AI agents to search and retrieve study data via natural language or direct tool calls.
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    MIT
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    Integrates GROMACS molecular dynamics simulations with VMD visualization, enabling setup, execution, analysis, and 3D visualization of molecular dynamics workflows through natural language.
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    MIT
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    Enables querying the EBI Expression Atlas for gene expression data across species and conditions. Part of the Pipeworx gateway, it provides access to baseline and differential expression studies.
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    MIT
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    An MCP server that enables language models to fetch protein information from the UniProt database, including protein details, sequences, functions, and structures.
    MIT
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    Reproduces the in-silico toxicological profile of Heracleum sosnowskyi metabolites from Rassabina & Fedorov (2025) using open-source models for LD50 prediction, toxicity classification, chemical space clustering, and synthesis cost estimation.
    MIT
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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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    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.
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    MIT
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    Enables querying of per-residue missense tolerance, Pfam domain annotations, and variant counts for human transcripts by wrapping the MetaDome web service. Provides MCP tools for resolving transcripts, requesting tolerance landscapes, and identifying constrained regions.
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    MIT