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    Enables LLMs and autonomous agents to calculate pulse arrival time, pulse transit time, pulse wave velocity, and arterial vascular compliance from dual-sensor timestamps through deterministic JSON-RPC tools. Supports continuous cuffless cardiovascular monitoring using a zero-dependency Python implementation.
    7
    MIT
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    Enables deterministic, non-invasive calculation of pre-ejection period and left ventricular ejection time, with rate-corrected indices and inotropic performance classification exposed as JSON-RPC tools for LLM and agent workflows.
    7
    MIT
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    An MCP server that lets an LLM answer a pharmacist's question about drug shortages by normalizing drug names, finding pharmacologic alternatives, and checking their shortage status using public FDA and NLM data.
    5
    MIT
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    Enables Claude Desktop to query and analyze diabetes data from Omnipod 5 and Glooko through natural language, providing clinical audit and triage insights such as time in range, trends, and bolus analysis.
    12
    MIT
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    Clinical research MCP server providing real-time access to PubMed (35M+ papers) and ClinicalTrials.gov (400K+ trials). Built for trial coordinators and life sciences teams. No API key required.
    3
    3
    MIT
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    Enables AI agents to retrieve cited pharmacogenomic and gene-variant information, including drug–gene guidance from CPIC/DPWG and rsID lookups, so responses can quote curated sources instead of relying on memory. A local package also lets users read raw DNA files on their own computer without sending the file data to the remote service.
    2
    39 PyPI
    MIT
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    Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.
    5
    37
    Apache 2.0
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    Enables AI assistants to rapidly gather and synthesize structural, chemical, conservation, and literature data about protein binding pockets for drug-target triage. Useful as a reconnaissance step before computational binder design.
    8
    1
    MIT
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    SuperGlookoQuery is a Claude Desktop extension (MCPB) that connects to Glooko diabetes device data and exposes it as clinical analysis tools (time in range, GMI, trends, enriched bolus/basal analysis, charting), for any pump/CGM combination Glooko supports rather than one fixed device. It's a fork of Richard Hall's podquery-mcp, reworked to discover each account's own data shape rather than assumi
    17
    MIT
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    A Model Context Protocol (MCP) server for searching the National Provider Identifier (NPI) registry. This server provides tools to search and retrieve information about healthcare providers and organizations in the United States.
    1
    35 PyPI
    4
    Python
    MIT
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    Enables Claude Desktop to securely access FreeStyle LibreLink continuous glucose monitoring data, providing real-time readings, historical analysis, and health insights through natural language queries.
    8
    15
    MIT
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    An MCP server that enables AI assistants to query U.S. FDA public datasets, including drug adverse events, labeling, recalls, approvals, shortages, NDC directory, and medical device regulatory information.
    10
    MIT
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    MCP server that lets AI assistants query current, dated information about PatientNotes, an AI medical scribe, covering pricing, features, languages, compliance, and competitor comparisons.
    6
    1
    MIT
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    Enables searching LOINC codes and retrieving detailed information including panel members and answer options via the LOINC Search API.
    2
    1
    MIT
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    Enables AI agents to read and analyze Dexcom CGM data through tools for current glucose, recent historical readings, and glucose statistics such as time in range.
    3
    MIT
  • F
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    Enables searching and retrieving detailed information from PubMed articles using the NCBI Entrez API. Supports configurable search parameters including title/abstract filtering and keyword expansion to find relevant scientific publications.
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    Connects DHIS2 health information systems to AI assistants via the Model Context Protocol, enabling natural language queries for analytics, metadata, and tracker data.
    13
    MIT
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    Upload your raw DNA file from 23andMe, AncestryDNA, MyHeritage, FamilyTreeDNA, or any VCF -- and watch a team of AI agents fan out across 16+ public genomics databases, share discoveries with each other in real time, and produce a comprehensive health report. Everything runs on your machine. Nothing is uploaded anywhere.
    24
    16
    MIT
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    Bridges your Nightscout CGM data with AI assistants via the Model Context Protocol, enabling natural language queries about glucose readings, treatments, statistics, and pattern analysis.
    21
    GPL 3.0
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    A Model Context Protocol server that provides AI agents with a unified interface for real-time EEG acquisition, replay, processing, visualization, recording, and stimulation from over 66 BrainFlow boards.
    47
    34 PyPI
    3
    BSD 3-Clause