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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 analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.
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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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    MIT
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    An MCP server that provides mouse genetics data from Mouse Genome Informatics (MGI), enabling LLM agents to query markers, mutations, alleles, phenotypes, and disease models.
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    MIT
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    Enables AI-driven pharmacogenomic analysis by querying structured genetic variant, drug response, and disease risk data. Supports natural language questions about medications, traits, and health risks based on user genome data, with privacy-first local execution.
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    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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    Enables unified access to 110 life science APIs and databases, including genomics, proteomics, chemistry, literature, and clinical data. Users can query genes, proteins, compounds, pathways, and more through natural language.
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    MIT
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    Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.
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    Apache 2.0
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    Provides a programmatic interface to the Genome Aggregation Database (gnomAD) API across versions v2.1.1, v3.1.2, and v4.1.0. It enables users to query gene metadata, variant information, population frequencies, and ClinVar data through a unified schema.
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    Apache 2.0
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    Enables LLM agents to query the CZ CELLxGENE Census single-cell atlas with ontology-aware filters, cost caps, and full provenance, allowing natural language questions about cell types, tissues, and gene expression.
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    MIT