Mmcp.market

ILO Labour Statistics (ILOSTAT): unemployment, wages, informality

by SidneyBissoli·io.github.SidneyBissoli/ilo-mcp-server·v0.6.1

Labour market data from the ILO (ILOSTAT) by country, year, sex and age, with provenance.

A86/100grade A
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A86/100

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1 stars310 downloads/wk

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Tools (6, 1 write)

write = sends, deletes, buys or posts
  • fetchFree

    Returns the full document for an id obtained from `search`, as { id, title, text, url, metadata }: `text` is the readable content (Markdown) and `url` the canonical public page to cite. Companion of `search` in the OpenAI Deep Research contract, over the ILOSTAT labour statistics (≈1,200 SDMX dataflows: employment, unemployment, wages, working time, informality, SDG labour indicators) catalog. Only ids returned by `search` are valid; an unknown id returns an error. The `ilo_*` tools remain the tools for data queries. Behavior: read-only and idempotent — a live GET against the public source when the document needs it.

  • ilo_get_dataFree

    Statistical observations from one ILOSTAT dataflow, filtered by dimension codes (filters, e.g. {"REF_AREA": ["BRA","ARG"], "SEX": "SEX_T"}) and period (start_period/end_period, e.g. "2015"/"2024"). REF_AREA is required, maximum 30 areas per call — for broad panels, split areas into batches and/or paginate by period. Unfiltered dimensions return all their categories. Does not aggregate, convert or otherwise transform values (raw ILOSTAT data only), and does not search indicators (use ilo_search_indicators).

  • ilo_get_indicator_metadatawrite actionFree

    Structure of one ILOSTAT dataflow: dimensions (in SDMX key order), their codelists, the time dimension, the source's default selection and the data vintage (last update at the ILO). Use before ilo_get_data to know which filters exist. Does not return statistical values and does not list the codes themselves (use ilo_list_dimension_values).

  • ilo_list_dimension_valuesFree

    Valid codes (id + label) of one dimension of an ILOSTAT dataflow — e.g. the country/area codes of REF_AREA (ISO 3166-1 alpha-3 such as BRA, plus X-codes for aggregates such as X01 World) or the categories of SEX (SEX_T/SEX_M/SEX_F) and AGE. Use `search` to resolve a name to a code (e.g. search "Brazil") instead of paging through hundreds of codes; codelists are shared across dataflows, so a code found here is valid wherever the same codelist is used. Use to build correct ilo_get_data filters. Does not return statistical values, does not say which codes actually have data for a given dataflow, and is not applicable to the time dimension (filter it via start_period/end_period in ilo_get_data).

  • ilo_search_indicatorsFree

    Search the ILOSTAT catalogue of ~1,200 indicator dataflows by keywords in the name or id (e.g. "unemployment rate sex age"). All terms must match (AND, case-insensitive), so start with 2–3 English words and drop terms if you get 0 results. Everyday and US wording is resolved to the ILO's own (labor→labour, wages/salary→earnings, informality→informal, gender→sex, productivity→output per worker); when that happens the response says so in vocabulary_notes. Results are ranked by ILO relevance weight, not by match count. Reading the id tells you the shape: suffix _RT = rate/ratio, _NB = number (usually thousands); dataflows whose second token starts with 2 (e.g. DF_UNE_2EAP_…) are ILO modelled estimates with full country/year coverage, the others are reported national data. Returns dataflow ids to use with ilo_get_data / ilo_get_indicator_metadata. Searches the local catalogue only — it does not return statistical values (use ilo_get_data), does not search dimension codes such as countries (use ilo_list_dimension_values) and does not cover non-ILO sources.

  • searchFree

    Searches the ILOSTAT labour statistics (≈1,200 SDMX dataflows: employment, unemployment, wages, working time, informality, SDG labour indicators) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched). This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools `search` and `fetch`. Pass one of the returned ids to `fetch` to read the document. For direct questions and for data (values, series, rankings) prefer the `ilo_*` tools, which return the actual data with provenance — this is a catalog index, not a data query. Query: natural language or keywords, Portuguese or English; accents and case are ignored. Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

Public scan report

scanner v0.1.3 · 2026-09-19 · same rubric, same numbers if you re-run it

1 high
  • Code scan27 source files scanned25/25
  • Live reliabilityremote reachable in 620ms20/20
  • Tool poisoning6 tool descriptions checked15/15
  • Auth qualityopen endpoint exposes 1 write-action tools with no auth3/15
  • Maintenancelast push 2 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Findings (1)

  • highWrite-action tools reachable without authenticationauth.open-write
Overall 86/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

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claude mcp add --transport http ilo-mcp-server https://ilo.sidneybissoli.com/mcp
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