Server data from the Official MCP Registry
Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.
About
Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.
Remote endpoints: streamable-http: https://gateway.pipeworx.io/czso-cz/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 (559/560 approved). 1 finding(s) downgraded by scanner intelligence.
23 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-czso-cz": {
"url": "https://gateway.pipeworx.io/czso-cz/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
mcp-czso-cz
Czech Statistical Office (Český statistický úřad, ČSÚ) open-data MCP.
Part of Pipeworx — an MCP gateway connecting AI agents to 1394+ 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.):
{
"mcpServers": {
"czso-cz": {
"url": "https://gateway.pipeworx.io/czso-cz/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 Czso Cz data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
Reviews
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