About Statec Lu
Statec Lu connects Luxembourg STATEC statistics to MCP for agents and applications that need official data. It provides dataset discovery, dimension metadata, and observation queries through Pipeworx or a local stdio server.
Key features
- 01Search the STATEC dataset catalogue
- 02Inspect dimensions and valid codes
- 03Filter observations with SDMX keys
- 04Return series with dimension labels
Use cases
- 01Find population or unemployment datasets
- 02Check dimension codes before building a query
- 03Retrieve observations for selected periods
MCP support
As an MCP server, it exposes dataset search, structure lookup, and observation retrieval tools. It can connect through the Pipeworx gateway or run locally over stdio.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://gateway.pipeworx.io/statec-lu/mcpclaude mcp add --transport http pipeworx-io-statec-lu https://gateway.pipeworx.io/statec-lu/mcp{"mcpServers":{"pipeworx-io-statec-lu":{"type":"http","url":"https://gateway.pipeworx.io/statec-lu/mcp"}}}Open in Cursor{"servers":{"pipeworx-io-statec-lu":{"type":"http","url":"https://gateway.pipeworx.io/statec-lu/mcp"}}}Open in VS Code{"mcpServers":{"pipeworx-io-statec-lu":{"type":"http","url":"https://gateway.pipeworx.io/statec-lu/mcp"}}}{"mcpServers":{"pipeworx-io-statec-lu":{"serverUrl":"https://gateway.pipeworx.io/statec-lu/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEmcp-statec-lu
STATEC (Institut national de la statistique et des études économiques du
Part of Pipeworx — an MCP gateway connecting AI agents to 1684+ live data sources.
Tools
| Tool | Description |
|---|---|
list_dataflows | Browse or keyword-search STATEC (Luxembourg statistics) datasets, called "dataflows". Each result has an id (e.g. "DF_A1100", the dataflowRef you pass to get_data / dataflow_structure) and an English name plus a short description (publication date, periodicity, author, category). STATEC publishes hundreds of datasets, so pass query to filter unless you really want the whole catalog. Example: list_dataflows({ query: "population" }) or list_dataflows({ query: "unemployment" }). |
dataflow_structure | Get the structure (Data Structure Definition) of one STATEC dataset: its ordered dimensions and, for each, the valid codes. Use this BEFORE get_data to learn how to build the dot-separated SDMX key. The key has one position per dimension, in dimension_order; an empty position is a wildcard. Example: dataflow_structure({ dataflow_id: "DF_A1100" }). |
get_data | Pull observations from a STATEC 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. Fetch dataflow_structure first to know the dimension order and valid codes. Example: get_data({ dataflow_id: "DF_A1100", key: "Valeur..A", start_period: "2010", end_period: "2020" }) picks VARIABLE=Valeur, wildcards SPECIFICATION, FREQ=A (annual). 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": {
"statec-lu": {
"url": "https://gateway.pipeworx.io/statec-lu/mcp"
}
}
}
What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/statec-lu/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1684+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
No MCP client? Call it over HTTP
curl -X POST https://gateway.pipeworx.io/v1/tools/statec_lu_list_dataflows \
-H 'Content-Type: application/json' \
-d '{"query":"population"}'
No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/statec_lu_list_dataflows. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.
Standalone (no gateway account)
This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:
{
"mcpServers": {
"statec-lu": {
"command": "npx",
"args": ["-y", "@pipeworx/mcp-statec-lu"]
}
}
}
Or run it directly to confirm it starts:
npx -y @pipeworx/mcp-statec-lu
It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call
for only this pack's tools — none of the shared meta-tools the gateway
connection above adds. Same source, same tools, no ask_pipeworx routing.
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Statec Lu data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.