Czso Cz

Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON ▾

No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself — its README, its docs, or a verified owner. We haven’t found those for Czso Cz, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.

Documentation Overview

mcp-czso-cz

Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.

Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.

Tools

Tool	Description
`list_datasets`	Browse the Czech Statistical Office (ČSÚ) open-data catalog of datasets ('datové sady'). Returns id (kod), version (verze), Czech title (nazev), status, and available time/territory levels. The full catalog is ~781 datasets; filter by a case-insensitive substring of the Czech title (the API has no server-side search) and page with limit/offset.
`dataset_detail`	Full catalog metadata for one ČSÚ dataset by id (kod): description, keywords, indicators (ukazatele), dimension variants (variantyDimenze), selection rules, update periodicity and themes. Catalog layer only — use data_summary / get_data for the actual numbers.
`data_summary`	Cheap content summary for a ČSÚ dataset from the data layer: number of data cells (pocetUdaju), covered time range (casovaDimenzeOd/Do), per-dimension value counts, and last-change/publish times. Use this before get_data to gauge size, since full datasets can be large. Version (verze) is auto-resolved from the catalog if omitted.
`get_data`	Fetch the actual observations/values for a ČSÚ dataset as JSON-stat 2.0 (dimensions in `id`/`dimension`, cell counts in `size`, numbers in `value`). Verified live. NOTE: returns the complete dataset as a full cross-product, which is often large (hundreds of thousands of cells, 1MB+) — call data_summary first to check pocetUdaju. Version (verze) is auto-resolved from the catalog if omitted.

Quick Start

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

config.json

{
  "mcpServers": {
    "czso-cz": {
      "url": "https://gateway.pipeworx.io/czso-cz/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/czso-cz/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:

config.json

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1476+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

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:

Code

ask_pipeworx({ question: "your question about Czso Cz data" })

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

License

MIT

Read the full README →View source on GitHub →

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Frequently Asked Questions about Czso Cz

We don't have a confirmed install command for Czso Cz yet, so we don't publish a generated one — a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/pipeworx-io/mcp-czso-cz) for the current steps.

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Technical Specs & Signals

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31Quality signal: Emerging · 31/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools11/30

Adoption & activity2/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Documentation Overview

mcp-czso-cz

Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.

Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.

Tools

Tool	Description
`list_datasets`	Browse the Czech Statistical Office (ČSÚ) open-data catalog of datasets ('datové sady'). Returns id (kod), version (verze), Czech title (nazev), status, and available time/territory levels. The full catalog is ~781 datasets; filter by a case-insensitive substring of the Czech title (the API has no server-side search) and page with limit/offset.
`dataset_detail`	Full catalog metadata for one ČSÚ dataset by id (kod): description, keywords, indicators (ukazatele), dimension variants (variantyDimenze), selection rules, update periodicity and themes. Catalog layer only — use data_summary / get_data for the actual numbers.
`data_summary`	Cheap content summary for a ČSÚ dataset from the data layer: number of data cells (pocetUdaju), covered time range (casovaDimenzeOd/Do), per-dimension value counts, and last-change/publish times. Use this before get_data to gauge size, since full datasets can be large. Version (verze) is auto-resolved from the catalog if omitted.
`get_data`	Fetch the actual observations/values for a ČSÚ dataset as JSON-stat 2.0 (dimensions in `id`/`dimension`, cell counts in `size`, numbers in `value`). Verified live. NOTE: returns the complete dataset as a full cross-product, which is often large (hundreds of thousands of cells, 1MB+) — call data_summary first to check pocetUdaju. Version (verze) is auto-resolved from the catalog if omitted.

Quick Start

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

config.json

{
  "mcpServers": {
    "czso-cz": {
      "url": "https://gateway.pipeworx.io/czso-cz/mcp"
    }
  }
}

What this endpoint actually serves

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

config.json

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1476+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

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:

Code

ask_pipeworx({ question: "your question about Czso Cz data" })

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

License

MIT

Frequently Asked Questions about Czso Cz