Server data from the Official MCP Registry
ILOSTAT (International Labour Organization statistics) MCP — global labour
About
ILOSTAT (International Labour Organization statistics) MCP — global labour
Remote endpoints: streamable-http: https://gateway.pipeworx.io/ilostat/mcp
Security Report
Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry. Trust signals: trusted author (576/577 approved). 1 finding(s) downgraded by scanner intelligence.
22 tools verified · Open access · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-pipeworx-io-ilostat": {
"url": "https://gateway.pipeworx.io/ilostat/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
mcp-ilostat
ILOSTAT (International Labour Organization statistics) MCP — global labour
Part of Pipeworx — an MCP gateway connecting AI agents to 1394+ live data sources.
Tools
| Tool | Description |
|---|---|
list_dataflows | Browse or keyword-search ILOSTAT datasets (dataflows) from the International Labour Organization. Each result has an id (the dataflowId you pass to get_data / dataflow_structure) and an English name. ILO publishes ~1,200 datasets covering employment, unemployment, labour force participation, wages, hours worked, informality, working poverty, child labour, and occupational safety. Always pass query to filter unless you really want the whole list. Example: list_dataflows({ query: "unemployment rate" }) or list_dataflows({ query: "minimum wage" }). |
dataflow_structure | Get the structure (Data Structure Definition) of one ILOSTAT dataset: its ordered dimensions and, for each, the valid codes. Use this to learn how to build the dot-separated SDMX key for get_data. The key positions correspond to the dimensions in order; an empty position is a wildcard. Common dimensions are REF_AREA (ISO3 country code, e.g. "USA", "FRA"), FREQ (A=annual, Q=quarterly, M=monthly), SEX, AGE, and MEASURE. Always call this before get_data. Example: dataflow_structure({ dataflow_id: "DF_SDG_0852_SEX_AGE_RT" }). |
get_data | Pull observations from an ILOSTAT dataset. key is a dot-separated SDMX dimension filter, one position per dimension in the order given by dataflow_structure; leave a position empty to wildcard it. ILO keys typically start with REF_AREA then FREQ; e.g. get_data({ dataflow_id: "DF_SDG_0852_SEX_AGE_RT", key: "USA.A...", start_period: "2015", end_period: "2024" }) selects the USA, annual frequency, and wildcards the remaining dimensions. Omit key (or pass "") to fetch all series — caution, this can be large. Returns decoded series with their dimension labels and per-period values. |
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"ilostat": {
"url": "https://gateway.pipeworx.io/ilostat/mcp"
}
}
}
Or connect to the full Pipeworx gateway for access to all 1394+ data sources:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English:
ask_pipeworx({ question: "your question about Ilostat data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
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