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robcerda

Oura MCP Server

by robcerda
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Python
Hybrid

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    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

    A3.8/5.0

    Scored across 22 tools

    Disambiguation5/5

    Every tool targets a distinct data resource or lifecycle step. Overlaps like get_daily_sleep, get_sleep_periods, get_sleep_time, and get_daily_summary are clearly differentiated by their descriptions (scores vs. detailed periods vs. recommended bedtime vs. combined summary). No two tools appear to serve the same purpose.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern using lowercase with underscores, predominantly 'get_' for data retrieval, with setup_authentication and check_auth_status as logical exceptions for auth flows. The pattern is predictable and uniform.

    Tool Count4/5

    22 tools is on the higher end but appropriate for a comprehensive health/activity API covering many distinct data types (sleep, activity, readiness, stress, HR, etc.). Each tool maps to a unique resource, and the count feels justified rather than bloated.

    Completeness5/5

    The server covers a wide range of Oura data: daily scores and contributors, detailed periods, workouts, sessions, tags, rest mode, personal info, ring hardware, and auth status. It also includes a convenient summary tool and a generic document retriever. For a read-focused API, there are no obvious gaps for typical agent use cases.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources