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rilhia

PodQuery

by rilhia
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Alternatives to PodQuery

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    Related Servers

    • LibreLink MCP Server

      amansk
      F
      license
      A
      quality
      D
      maintenance
      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
      14
      -

    • SuperGlookoQuery

      sikcapri
      A
      license
      A
      quality
      A
      maintenance
      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
      2
      16
      MIT

    • dexcom-mcp

      sobek34
      F
      license
      Not graded
      quality
      D
      maintenance
      Enables reading real-time continuous glucose monitor data from Dexcom sensors via the Share API, allowing Claude to access glucose levels, trends, and statistics.
      -
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.5/5.0

    Scored across 12 tools

    Disambiguation4/5

    Each tool targets a distinct analytical granularity — hourly patterns, whole-window aggregates, bucketed trends, raw readings, bolus events, settings history — and the descriptions cross-reference each other well. The only real ambiguity is get_chart_series vs get_chart_html, both chart-oriented, though their descriptions clearly separate 'data to render' from 'already-rendered chart'.

    Naming Consistency5/5

    Every tool follows the same get_<noun> pattern with descriptive, specific suffixes (hourly_trends, enriched_bolus_log, meal_window_analysis). No mixed conventions or vague verbs.

    Tool Count5/5

    Twelve tools cover glucose, insulin, basal, settings, device events, meal analysis, and charting without feeling padded. Each tool earns its place; the count is well within the ideal range for a diabetes data query server.

    Completeness5/5

    The surface covers the read-only diabetes domain thoroughly: raw and aggregated glucose, insulin at both daily and event level, basal delivery states, settings history, device changes, meal-window analysis, and two chart outputs. There are no obvious dead ends or critical missing operations for the stated purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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