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Provenance-first MCP server for ILOSTAT (ILO labour statistics) — remote, Cloudflare Workers

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Last scanned: 10/3/2026
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/SidneyBissoli/ilo-mcp-server
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "ilo": {
      "command": "node",
      "args": ["/path/to/ilo-mcp-server/dist/index.js"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/SidneyBissoli/ilo-mcp-server and follow its README for install instructions.
Use cases

MCP Servers overview

# ILO Labour Statistics (ILOSTAT) — MCP Server

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🇧🇷 [Leia em Português](https://github.com/SidneyBissoli/ilo-mcp-server/blob/main/LEIA-ME.md)

A **public, hosted, provenance-first** [MCP](https://modelcontextprotocol.io) 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](#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](https://github.com/SidneyBissoli/ilo-mcp-server/blob/main/LEIA-ME.md).

## 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.

| 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 |

## 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`](https://github.com/SidneyBissoli/ilo-mcp-server/blob/main/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](https://ilostat.github.io/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 — a whole table, repeatedly, for analysis |
| [sdmx1](https://pypi.org/project/sdmx1/) 2.27.0 / [pandaSDMX](https://pypi.org/project/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](https://db.nomics.world/ILO) (API, `dbnomics` for Python, [rdbnomics](https://cran.r-project.org/package=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](https://ilostat.ilo.org/resources/sdmx-tools/) | 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 → 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](https://ibge.sidneybissoli.com) (Brazilian statistics),
[BCB](https://bcb.sidneybissoli.com) (Central Bank of Brazil),
[Senado](https://senado.sidneybissoli.com) (Brazilian Senate open data),
[SIH/SUS](https://sih.sidneybissoli.com) (Brazilian hospital admissions) and
[medical terminologies](https://medical.sidneybissoli.com) (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:

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

For clients that launch MCP servers as a command, use the
[`mcp-remote`](https://www.npmjs.com/package/mcp-remote) bridge:

```json
{
  "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:<DATAFLOW_ID>`, 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`](https://www.npmjs.com/package/ilo-mcp-server), Node ≥ 20):

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

Or from source:

```bash
git clone https://github.com/SidneyBissoli/ilo
claudecursoremploymentiloilostatlabor-statisticslabour-statisticsmcpmcp-servermodel-context-protocolopen-dataprovenancesdmxtypescriptunemploymentwages

What people ask about ilo-mcp-server

What is SidneyBissoli/ilo-mcp-server?

+

SidneyBissoli/ilo-mcp-server is mcp servers for the Claude AI ecosystem. Provenance-first MCP server for ILOSTAT (ILO labour statistics) — remote, Cloudflare Workers It has 1 GitHub stars and its last recorded update is dated 2026-10-02.

How do I install ilo-mcp-server?

+

You can install ilo-mcp-server by cloning the repository (https://github.com/SidneyBissoli/ilo-mcp-server) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is SidneyBissoli/ilo-mcp-server safe to use?

+

Our security agent has analyzed SidneyBissoli/ilo-mcp-server and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains SidneyBissoli/ilo-mcp-server?

+

SidneyBissoli/ilo-mcp-server is maintained by SidneyBissoli. The last recorded GitHub activity is dated 2026-10-02, with 0 open issues.

Are there alternatives to ilo-mcp-server?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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