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CalisthenicsCompanion-MCP

by Packi1992
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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

    A4.3/5.0

    Scored across 19 tools

    Disambiguation4/5

    The read-path tools (get_training_state, get_stats, get_adherence, get_progress, get_history) share statistical scope, but each has explicit carve-outs for what it does and does not return, which prevents serious misselection. The propose_* and suggestion tools are cleanly distinct from each other and from the reads.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern: get_* for reads, list_* for collections, propose_* for proposals, set_* for parameters, and withdraw_* for the one mutating exception. There is no mixed casing or vague verb usage.

    Tool Count4/5

    At 19 tools, the server is slightly above the ideal 3-15 band, but the count is justified by the breadth of the coach workflow: reads, analytics, parameters, proposals, and suggestion management. The set feels dense rather than bloated.

    Completeness5/5

    The tool surface covers the full coach workflow: raw history, computed training state, adherence, progress, templates, planned workouts, catalog, coach parameters, and proposal-based changes for plans, exercises, and calendar events, plus suggestion lifecycle management. Intentional gaps like accept/reject are external to the MCP boundary and clearly documented.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources