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ILO Statistics (ILOSTAT) MCP Server

by SidneyBissoli
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TypeScript
Remote

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TDQS

A4.2/5.0

Scored across 6 tools

Disambiguation3/5

The four ilo_* tools are cleanly separated (catalogue search, metadata, dimension codes, data values). However, ilo_search_indicators and the bare search tool both search the same ~1,200-dataflow ILOSTAT catalogue and can easily be mistaken for each other; the descriptions differentiate them (ILO dataflow ids vs. Deep Research document ids) but the overlap is a real misselection risk. fetch vs. ilo_get_indicator_metadata is less ambiguous since one returns document text and the other structural metadata.

Naming Consistency3/5

The ilo_ prefixed tools follow a clear verb_noun pattern (ilo_search_indicators, ilo_get_indicator_metadata, ilo_list_dimension_values, ilo_get_data). The two contract tools break the convention with bare single-verb names (search, fetch) and no prefix, creating a mixed scheme. It remains readable and the split is explained, but conventions are not uniform.

Tool Count4/5

Six tools is well within a healthy range for a statistical data server and each has a defined role. The only slight redundancy is the search/fetch pair layering a generic document-retrieval contract over an already data-focused surface, which costs a little tightness.

Completeness4/5

The data workflow is fully covered: find a dataflow (ilo_search_indicators), inspect its dimensions (ilo_get_indicator_metadata), resolve codes (ilo_list_dimension_values), then pull observations (ilo_get_data), with search/fetch adding document retrieval. Minor gaps exist (no bulk multi-dataflow query, no transforming/aggregating helper) but these are explicitly declared out of scope and can be worked around.

Maintenance

ActivityActive
ResponsivenessNo issues

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