tslab-mcp
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genpark-time-seriesofficial
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TDQS
Scored across 8 tools
Each tool has a distinct and well-defined purpose within the time series forecasting workflow: loading, describing, listing models, cross-validating, forecasting, detecting anomalies, and exporting results. There is no overlap or ambiguity between tools.
All tools follow a consistent pattern: the prefix 'tsf_' followed by a verb (and optional noun), all in snake_case. Examples include tsf_load_series, tsf_describe_series, tsf_cross_validate, and tsf_export_report. The naming is predictable and uniform.
With 8 tools, the server covers a complete analysis pipeline without excess. Each tool is necessary and corresponds to a clear step in the workflow, from data loading to report generation. The count is well-scoped for the domain.
The tool surface covers the full lifecycle of a typical time series analysis: load data, explore features, check available models, cross-validate, forecast, detect anomalies, and export manifests/reports. There are no obvious gaps; the workflow feels self-contained and actionable.