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Datacube Sk

Official registry Data and databases

DATAcube — Statistical Office of the Slovak Republic (data.statistics.sk).

Source code Website Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http datacube-sk 'https://gateway.pipeworx.io/datacube-sk/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "datacube-sk": {
            "type": "http",
            "url": "https://gateway.pipeworx.io/datacube-sk/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. mcp-datacube-sk
  2. Tools
  3. Quick Start
  4. No MCP client? Call it over HTTP
  5. Standalone (no gateway account)
  6. Using with ask_pipeworx
  7. More
  8. License

mcp-datacube-sk

DATAcube — Statistical Office of the Slovak Republic (data.statistics.sk).

Part of Pipeworx — an MCP gateway connecting AI agents to 1854+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

Tools

ToolDescription
list_datasetsBrowse / search the DATAcube collection of Slovak statistical cubes. Filter by case-insensitive substring of the English label. Returns each matching cube's code (use it as cube in the other tools), label, last update date, and its ordered list of dimension codes.
dataset_dimensionsList the dimensions of one cube, in path order, with each dimension's valid value codes and labels. Selections in get_data are positional and must follow this dimension order. Get the cube code from list_datasets.
get_dataPull data for a cube as JSON-stat. Provide one selection per dimension, in the dimension order returned by dataset_dimensions. Each selection is either a single value code, a comma-separated list of codes (e.g. "SEX_M,SEX_F"), or the literal "all" for every value of that dimension. The number of selections must equal the cube's dimension count. Output is JSON-stat: value is the flat data array, dimension/size/id describe its shape.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "datacube-sk": {
      "url": "https://gateway.pipeworx.io/datacube-sk/mcp"
    }
  }
}
What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/datacube-sk/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 1854+ 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/datacube_sk_list_datasets \
  -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/datacube_sk_list_datasets. 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": {
    "datacube-sk": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-datacube-sk"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-datacube-sk

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 Datacube Sk data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

Frequently asked questions

What is Datacube Sk?

DATAcube — Statistical Office of the Slovak Republic (data.statistics.sk).

How do I install Datacube Sk?

It runs as a remote server. In Claude Code: claude mcp add --transport http datacube-sk 'https://gateway.pipeworx.io/datacube-sk/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Datacube Sk need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Datacube Sk open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Datacube Sk?

It is published by pipeworx-io. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.