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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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    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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    Enables interaction with the CEDAR metadata repository, including fetching templates, searching BioPortal ontology terms, and managing template instances.
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    MIT
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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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    Enables AI assistants to search, browse, analyze, and export biological pathway data from Reactome through natural language.
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    Apache 2.0
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    Enables Claude Desktop to read and drive analyses on the active MilliMap session, including datasets, clusters, annotations, and markers.
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    MIT
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    Enables AI agents and applications to search, retrieve, and analyze chemical compounds, substances, and bioassays from PubChem's vast chemical information database through comprehensive tools for chemical research and discovery.
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    Apache 2.0
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    Enables AI-assisted molecular biology experiment design with tools for qPCR primer design, cloning strategy optimization, TaqMan probe design, and multiplex compatibility analysis.
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    MIT
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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.
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    MIT
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    Enables AI coding agents to search academic papers, resolve biomedical entities, mine relations, and traverse citation graphs using Semantic Scholar and PubTator3, with local caching for reproducibility.
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    MIT
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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
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    Converts messy metabolite names into standard database identifiers (KEGG, HMDB, ChEBI, PubChem, InChIKey) and performs crosswalking to Mouse-GEM for metabolic model input, with deterministic tools and an LLM reasoning layer for identity disambiguation.
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    MIT