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

ILO Labour Statistics (ILOSTAT) — MCP Server

🇧🇷 Leia em Português

A public, hosted, provenance-first MCP server for the International Labour Organization (ILO) statistics — the ILOSTAT database — 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 — not affiliated with or endorsed by the International Labour Organization.

Data remain © 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) — exact figures with an audit trail, not numbers guessed from training data.

🇧🇷 Em português. Servidor MCP remoto e hospedado (nada para instalar, sem conta e sem

chave) para as estatísticas de mercado de trabalho da OIT — desemprego, emprego, salários,

jornada e informalidade por país, ano, sexo e idade, direto no Claude, no ChatGPT ou em

qualquer cliente MCP, com proveniência e citação da fonte em cada resposta:

README em português.

Questions it answers

In plain language, inside the MCP client — the assistant picks the tool and the filters:

• "What has happened to unemployment in Brazil since 2015?" (ilo_get_data)
• "Compare youth unemployment in Brazil, Mexico and South Africa." (ilo_compare_countries)
• "How large is the gender pay gap, and where does the ILO publish it?" (ilo_search_indicators → ilo_get_data)
• "What share of employment in India is informal?" (ilo_search_indicators → ilo_get_data)
• "Which ILOSTAT dataflow has average monthly earnings by sex and economic activity?" (ilo_search_indicators)
• "Which country, age and sex codes can I filter this indicator by?" (ilo_list_dimension_values)
• "Give me a labour-market profile of Viet Nam." (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 — 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.

Comparison with the alternatives

Anyone who already works with ILOSTAT has good tools, and this server replaces none of them — 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.

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 → UNESCO UIS, national accounts → 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).

Use it (hosted — no setup)

Point any MCP client at the Streamable HTTP endpoint:

https://ilo.sidneybissoli.com/mcp

Claude Desktop / Claude Code and other clients with native remote support:

{

"mcpServers": { "ilostat": { "url": "https://ilo.sidneybissoli.com/mcp" } } }

For clients that launch MCP servers as a command, use the mcp-remote bridge:

{

"mcpServers": { "ilostat": { "command": "npx", "args": ["-y", "mcp-remote", "https://ilo.sidneybissoli.com/mcp"] } } }

The ilo-mcp-server.sidneybissoli.workers.dev hostname is also served, as a secondary.

ChatGPT (Deep Research)

ChatGPT deep research (and company knowledge, and research workflows over the Responses API) only uses an MCP server that exposes exactly search and fetch — this server does, on top of the ilo_* tools. Point the connector at the hosted endpoint, no key required:

https://ilo.sidneybissoli.com/mcp

search ranks the query against the full ILOSTAT dataflow catalogue (~1,200 SDMX dataflows — employment, unemployment, wages, working time, informality, SDG labour indicators) and returns { id, title, url } (ind: , e.g. ind:DF_UNE_2EAP_SEX_AGE_RT); fetch returns the dataflow as readable Markdown — name, data vintage, dimensions and codelists, the ILO's default selection and how to query it with ilo_get_data — 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 → Security and login → Developer mode) any tool is callable — the ilo_* tools remain the ones to use for data.

Run locally (stdio)

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 — same 6 tools, resources and prompts, same limits, same provenance block, no Cloudflare in the loop.

No install needed — the package is on npm (ilo-mcp-server, Node ≥ 20):

{

"mcpServers": { "ilostat": { "command": "npx", "args": ["-y", "ilo-mcp-server"] } } }

Or from source:

git clone https://github.com/SidneyBissoli/ilo-mcp-server

cd ilo-mcp-server npm install npm run build node dist/cli.js # serves MCP over stdio (Ctrl+C to stop)

(then point the client at node /path/to/ilo-mcp-server/dist/cli.js).

Differences from the hosted server, all due to the absence of Cloudflare bindings: the SDMX cache lives in process memory (structures and codelists are reused within a session, not across sessions); the search catalogue is downloaded from the official endpoint on the first search (its real retrieved_at is reported in provenance); no usage metrics, rate limit or auth. Logs go to stderr — stdout carries only the JSON-RPC stream. The repository Dockerfile builds this runtime (used by the Glama registry).

Tools

| search | ChatGPT Deep Research contract: ranks a query against the full dataflow catal