Labour statistics from ILOSTAT (ILO) with full provenance: source URL, vintage, license.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by ILOSTAT β ILO Labour Statistics (provenance First).
ilo_search_indicatorskeyword search over ~1,210 dataflows (paginated by `offset`)
ilo_get_indicator_metadatadimensions, codelists, vintage and default selection of a dataflow
ilo_list_dimension_valuesvalid codes of one dimension (paginated by `offset`)
ilo_get_dataobservations filtered by dimension and period
searchChatGPT Deep Research contract: ranks a query against the full dataflow catalogue, returns `{ id, title, url }` (`ind:<DATAFLOW_ID>`)
fetchChatGPT Deep Research contract: one dataflow as readable Markdown with the public data explorer page as `url
π§π· Leia em PortuguΓͺs
A public, hosted, provenance-first MCP server for the International Labour Organization (ILO) statistics β the ILOSTAT database β no installation, no account, no API key. Point your MCP client at the hosted endpoint and ask about unemployment, employment, wages, working time and other labour indicators by country, year, sex and age. It runs on Cloudflare Workers over Streamable HTTP and talks to the official ILOSTAT SDMX REST API.
Independent project. This is an unofficial, community-built client of the ILO's public ILOSTAT API β not affiliated with or endorsed by the International Labour Organization. Data remain Β© ILO under CC BY 4.0; see Data license and attribution.
Every response carries a provenance block (source URL, data vintage, real retrieval timestamp, license, ILO citation) β exact figures with an audit trail, not numbers guessed from training data.
π§π· Em portuguΓͺs. Servidor MCP remoto e hospedado (nada para instalar, sem conta e sem chave) para as estatΓsticas de mercado de trabalho da OIT β desemprego, emprego, salΓ‘rios, jornada e informalidade por paΓs, ano, sexo e idade, direto no Claude, no ChatGPT ou em qualquer cliente MCP, com proveniΓͺncia e citaΓ§Γ£o da fonte em cada resposta: README em portuguΓͺs.
In plain language, inside the MCP client β the assistant picks the tool and the filters:
ilo_get_data)ilo_compare_countries)ilo_search_indicators β ilo_get_data)ilo_search_indicators β ilo_get_data)ilo_search_indicators)ilo_list_dimension_values)ilo_country_labour_profile)Ask in your words, not the ILO's. ILOSTAT is worded in British statistical English, and the catalogue is matched on the dataflow name β so the everyday or US word used to return nothing at all. Measured over the 1,212 dataflows of the official catalogue (2026-09-13), and fixed since 0.6.0: the search translates the term and tells you it did.
| you ask | hits before | ILOSTAT writes | hits |
|---|---|---|---|
labor, labor force | 0 | labour, labour force | 176, 122 |
wages, salary | 0 | earnings | 107 |
informality | 0 | informal | 133 |
gender | 2 | sex | 1,131 |
productivity | 0 | output per worker | 4 |
jobless | 0 | unemployment | 108 |
Anyone who already works with ILOSTAT has good tools, and this server replaces none of them β
it sits somewhere else in the chain: it answers the question at the point where the question is
asked, inside the assistant, with source, vintage and licence attached to the answer. Detail,
side-by-side examples and the measured numbers in
docs/alternatives.md.
| Tool | What it is | When to prefer it |
|---|---|---|
| ilo-mcp-server (this) | Remote MCP server, hosted, nothing to install: 6 tools over the ~1,200 ILOSTAT dataflows, with a provenance block per answer | The question is asked in an assistant (Claude, ChatGPT, Cursor, Claude Code) and the answer has to be auditable |
| Rilostat 2.5.0 (R, CRAN) | The ILO's own R package, written by ILO staff: bulk download, metadata, filtering and reshaping | You are in R and want the dataset in a data frame β a whole table, repeatedly, for analysis |
| sdmx1 2.27.0 / pandaSDMX 1.10.0 (Python) | Generic SDMX clients; ILO is one of ~36 sources they know | Your pipeline is Python and you want SDMX objects, or the same code across several SDMX agencies |
DBnomics (API, dbnomics for Python, rdbnomics 0.6.4 for R) | Aggregator that republishes 1,071 ILO datasets next to other providers, one API for all | You want ILO series alongside IMF, OECD, Eurostat in a single interface |
| ILOSTAT SDMX REST API | The source itself, which this server calls | You are building your own client and want full control |
Do not use this server when you need a whole dataset rather than an answer (Rilostat's bulk download is the right tool), when the question is not labour statistics published by the ILO (education β UNESCO UIS, national accounts β IMF/World Bank), or when you need microdata: ILOSTAT publishes aggregates, and so does this server.
Sister servers, same design and same provenance block, for other official sources: IBGE (Brazilian statistics), BCB (Central Bank of Brazil), Senado (Brazilian Senate open data), SIH/SUS (Brazilian hospital admissions) and medical terminologies (ICD-11, ICD-10, LOINC, RxNorm, ATC, MeSH).
Point any MCP client at the Streamable HTTP endpoint:
Claude Desktop / Claude Code and other clients with native remote support:
For clients that launch MCP servers as a command, use the
mcp-remote bridge:
The ilo-mcp-server.sidneybissoli.workers.dev hostname is also served, as a secondary.
ChatGPT deep research (and company knowledge, and research workflows over the Responses API) only uses an MCP server that exposes exactly search and fetch β this server does, on top of the ilo_* tools. Point the connector at the hosted endpoint, no key required:
search ranks the query against the full ILOSTAT dataflow catalogue (~1,200 SDMX dataflows β employment, unemployment, wages, working time, informality, SDG labour indicators) and returns { id, title, url } (ind:<DATAFLOW_ID>, e.g. ind:DF_UNE_2EAP_SEX_AGE_RT); fetch returns the dataflow as readable Markdown β name, data vintage, dimensions and codelists, the ILO's default selection and how to query it with ilo_get_data β with the public ILOSTAT data explorer page as url, which is what ChatGPT cites. Both carry the same provenance block as every other tool, in structuredContent and _meta (the text channel is the contract's JSON). In ChatGPT's developer mode (Settings β Security and login β Developer mode) any tool is callable β the ilo_* tools remain the ones to use for data.
Prefer not to route queries through a third-party host? The same server also runs as a local stdio process that talks directly to the official ILOSTAT API β same 6 tools, resources and prompts, same limits, same provenance block, no Cloudflare in the loop.
No install needed β the package is on npm (ilo-mcp-server, Node β₯ 20):
Or from source:
Factual signals from GitHub, npm, and our automated checks β not a rating.
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