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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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    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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    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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    BSD 3-Clause
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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-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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    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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    Provides LLMs with structured access to critical biomedical databases including PubTator3 (PubMed/PMC), ClinicalTrials.gov, and MyVariant.info through the Model Context Protocol.
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    MIT
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    Enables gene set enrichment analysis using the Enrichr API across hundreds of gene set libraries including Gene Ontology, pathways, diseases, tissues, drugs, and transcription factors. Returns only statistically significant results for interpretation.
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    MIT
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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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