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RohanSingh02

forecast-mcp

by RohanSingh02
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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

    A4/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool targets a distinct action: listing, classifying, forecasting, evaluating, recommending, and explaining. There is no overlap between classification and explanation, and forecast_series complements rather than duplicates classify_demand_pattern.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (list_skus, classify_demand_pattern, forecast_series, evaluate_forecast, recommend_replenishment, explain_forecast). No mixed conventions or vague verbs.

    Tool Count5/5

    Six tools is well within the 3-15 range and each covers an essential function for the forecasting domain. The set feels neither sparse nor bloated.

    Completeness4/5

    The set covers the core workflow: listing SKUs, classifying demand, forecasting, backtesting, replenishment, and explanation. A minor gap is lack of a dedicated tool to inspect raw historical demand data, but agents can work around it via the other tools.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources