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srs-mcp

by happymario123
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Python
Local

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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

    A4.2/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool serves a clearly distinct purpose: adding items, fetching due items, grading recall, viewing stats, exporting data, and forecasting workload. There is no overlap or ambiguity in their intended actions.

    Naming Consistency5/5

    Every tool follows a consistent verb_noun pattern (add_item, get_due_items, grade_item, get_stats, export_items, get_forecast), making it easy to infer the action and target. No mixed conventions or vague verbs.

    Tool Count5/5

    With 6 tools, the server is well-scoped for a spaced-repetition system, covering the core workflows (add, review, stats, export, forecast) without unnecessary bloat or excessive granularity.

    Completeness4/5

    The tool surface covers the primary lifecycle (add, review, stats, export, forecast) well, but lacks direct update and delete operations for items. Export tools can serve as a workaround, so the gap is minor.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources