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

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

- name: io.github.SidneyBissoli/ilo-mcp-server
- version: 1.6.4
- connection class: R0 (autonomous)
- trust: 97/100
- quality: 89/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.SidneyBissoli%2Filo-mcp-server
- tools: https://api.protogrid.dev/v1/servers/io.github.SidneyBissoli%2Filo-mcp-server/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "ilo-mcp-server": {
      "type": "http",
      "url": "https://ilo.sidneybissoli.com/mcp"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 99
- freshness: 100
- provenance: 90
- drivers: +repository +namespace-matches-repo +website +reachable +uptime-97% +updated-5d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 89/100 (good)

### protocol: 88 (weight 25)

- pass `protocol.modern`: supports 2026-07-28 (server/discover)
- pass `protocol.stateless`: answers without a session
- pass `protocol.transport`: streamable HTTP
- warn `protocol.list_ttl`: tools/list declares ttlMs 0, so clients re-fetch it on every use

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 93 (weight 30)

- pass `tools.descriptions`: every tool has a description
- warn `tools.description_length`: 1 tools have descriptions over 1,024 characters, which crowds the context
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 6 of 6 tools declare readOnlyHint or destructiveHint
- pass `tools.directory_hints`: every tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
- pass `tools.token_cost`: about 2,385 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 75 (weight 15)

- warn `stability.changes`: 22 tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: 100 (weight 15)

- pass `deps.known_vulns`: no known advisory in 7 resolved packages
- pass `deps.mcp_sdk_version`: @modelcontextprotocol/server 2.3.1, no known advisory
- pass `deps.resolvable`: ilo-mcp-server@1.6.4 resolved: 7 packages

- tools: 6, about 2,385 tokens to load them all
- tool set hash: 1ea0ed11e42083a6cafd813aee780c34
- tools last changed: 2026-10-09T01:27:04.298Z
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.SidneyBissoli/ilo-mcp-server.svg)](https://protogrid.dev/servers/io.github.SidneyBissoli/ilo-mcp-server)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-09 `fetch` changed (outputSchema)
- 2026-10-09 `search` changed (outputSchema)
- 2026-10-09 `ilo_get_data` changed (outputSchema)
- 2026-10-09 `ilo_list_dimension_values` changed (outputSchema)
- 2026-10-09 `ilo_get_indicator_metadata` changed (outputSchema)
- 2026-10-09 `ilo_search_indicators` changed (outputSchema)
- 2026-10-08 `ilo_get_data` changed (description)
  - before: 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): read each value with the unit and multiplier the ILO states in its row attributes (UNIT_MEASURE, UNIT_MULT — e.g. UNIT_MULT 3 = thousands). Does not search indicators (use ilo_search_indicators).
  - after: 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): read each value with the unit and multiplier the ILO states in its row attributes (UNIT_MEASURE, UNIT_MULT — e.g. UNIT_MULT 3 = thousands). Read TIME_PERIOD with the FREQ column (annual, quarterly or monthly) and OBS_STATUS when present (break in series, estimated or provisional value). Values are the current release, dated by data_vintage (the dataflow LAST_UPDATE): the ILO revises published figures and re-estimates modelled series (_2 ids) at each release, past years included. Does not search indicators (use ilo_search_indicators).
- 2026-10-06 `fetch` changed (outputSchema)
- 2026-10-06 `search` changed (outputSchema)
- 2026-10-06 `ilo_get_data` changed (outputSchema)

Full history: https://api.protogrid.dev/v1/servers/io.github.SidneyBissoli%2Filo-mcp-server/changes

## Dependencies

- npm ilo-mcp-server@1.6.4: resolved, 6 dependencies, MCP SDK @modelcontextprotocol/server 2.3.1

Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0.

## Remotes

- https://ilo.sidneybissoli.com/mcp (streamable-http, auth none, reachable true, uptime30d 0.9741379)

## Packages

- npm ilo-mcp-server@1.6.4

## Tools (6)

- `fetch`: 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_data`: 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): read each value with the unit and multiplier the ILO states in its row attributes (UNIT_MEASURE, UNIT_MULT — e.g. UNIT_MULT 3 = thousands). Read TIME_PERIOD with the FREQ column (annual, quarterly or monthly) and OBS_STATUS when present (break in series, estimated or provisional value). Values are the current release, dated by data_vintage (the dataflow LAST_UPDATE): the ILO revises published figures and re-estimates modelled series (_2 ids) at each release, past years included. Does not search indicators (use ilo_search_indicators).
- `ilo_get_indicator_metadata`: 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_values`: 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_indicators`: 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.
- `search`: 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.