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    An MCP server that connects AI assistants to OpenEMR instances to manage patient records, clinical trends, and medication safety. It provides 17 tools for tasks such as patient search, drug interaction checks, and generating comprehensive health trajectories and visit preparations.
    17
    MIT
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    Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.
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    MIT
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    Automatically analyzes and dispatches user tasks to appropriate handlers, supporting development task processing via Miyabi Agent and medical AI academic article generation. Provides intelligent task classification and routing for development, writing, and general tasks.
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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.
    MIT
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    This MCP server provides authoritative medical data from FDA, WHO, PubMed, RxNorm, and Google Scholar, enabling drug information lookup, health statistics retrieval, medical literature searching, and clinical guidelines access directly in AI workflows.
    70
    MIT
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    Provides AI-powered medical image analysis tools for LLM agents, enabling tasks such as X-ray classification, interactive segmentation, and visual question answering. It supports multi-step diagnostic reasoning and clinical workflows through a suite of specialized medical AI models.
    MIT
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    Provides comprehensive medical information by querying authoritative sources including FDA drug database, WHO health statistics, PubMed literature, RxNorm nomenclature, Google Scholar, and Australia's PBS API through 22+ specialized tools.
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    MIT
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    Exposes tools from the Ecuro Light API for managing clinical appointments, patient records, and clinic availability. It enables users to perform healthcare management tasks such as scheduling, patient search, and report generation through MCP-compatible clients.
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    Enables natural language interaction for scRNA-Seq analysis including preprocessing, clustering, and visualization using the CellRank library. It allows users and agents to perform complex genomic data tasks through standard MCP clients and frameworks.
    2