# Istat It [Health: Active]

**Category:** 🧮 Data Science Tools  
**Repository:** https://github.com/pipeworx-io/mcp-istat-it  
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**Directory Page:** https://allmcps.com/mcp/istat-it

## Description
ISTAT (Istituto Nazionale di Statistica) MCP — Italy's national statistics

## Tools
Capabilities this server exposes over MCP:

- **list_dataflows** — Browse or keyword-search ISTAT datasets (dataflows). Each result has an `id` (the dataflowId you pass to get_data / dataflow_structure) and an English name. ISTAT publishes ~4,800 datasets, so always pass `query` to filter unless you really want the whole list. Example: list_dataflows({ query: "une…
- **dataflow_structure** — Get the structure (Data Structure Definition) of one ISTAT 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. Example: dataf…
- **get_data** — Pull observations from an ISTAT 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. Example: get_data({ dataflow_id: "101_1015", key: "A.IT...", start_period: "2021", end_period: "2023"…

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `npx` (confidence: high):

```json
"mcpServers": {
  "istat-it": {
    "command": "npx",
    "args": ["-y","@pipeworx/mcp-istat-it"]
  }
}
```

## Documentation

## What Istat It MCP server does

Istat It MCP server provides MCP access to datasets published by Istituto Nazionale di Statistica, Italy’s national statistics institute. Its three pack-specific tools cover dataset discovery, schema inspection, and data retrieval.

`list_dataflows` browses or searches ISTAT dataflows by keyword. Results include a dataflow identifier and an English dataset name. Because ISTAT publishes roughly 4,800 datasets, keyword filtering is generally more practical than requesting the complete catalog.

`dataflow_structure` returns the structure of one dataset. It identifies the ordered dimensions and the valid codes for each dimension, which are needed to construct a query key.

`get_data` retrieves observations from a selected dataflow. Results contain decoded series, dimension labels, and values for each period.

## How it works

A typical query starts with `list_dataflows`, using a term such as unemployment or GDP to find a relevant dataflow. Pass the returned identifier to `dataflow_structure` to learn the exact dimension order and available codes.

Build the `get_data` `key` as a dot-separated SDMX filter with one position for every dimension, in the order reported by the structure tool. Leave a position empty to use a wildcard. For example, a key such as `A.IT...` selects annual data for Italy while leaving later dimensions unrestricted. `start_period` and `end_period` can limit the requested time range.

Omitting the key, or providing an empty key, requests all series in the dataflow. That may produce a large response, so filtered keys and period bounds are preferable when the dataset contains many combinations.

## Setup and configuration

Istat It MCP server can be added to an MCP client through the hosted Pipeworx endpoint:

```json
{
  "mcpServers": {
    "istat-it": {
      "url": "https://gateway.pipeworx.io/istat-it/mcp"
    }
  }
}
```

The README names Claude Desktop, Cursor, and Windsurf as clients that can use this configuration. The hosted endpoint does not require an account for the first calls. It also exposes Pipeworx shared meta-tools in addition to the pack tools, including routing through `ask_pipeworx`.

For a local connection, run the package with `npx`:

```json
{
  "mcpServers": {
    "istat-it": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-istat-it"]
    }
  }
}
```

The local process communicates through stdin and stdout and provides only the Istat It tools. No environment variables or Pipeworx account are specified as required.

## Tools and capabilities

- Search ISTAT dataflows by keyword.
- Inspect dimensions and valid codes for a dataflow.
- Construct SDMX dimension keys from dataset structure information.
- Retrieve observations for selected series and periods.
- Call the hosted tools directly over HTTP when an MCP client is unavailable.

The hosted HTTP interface includes endpoints such as `POST https://gateway.pipeworx.io/v1/tools/istat_it_list_dataflows`, using a JSON request body with a `query` field.

## Limitations and notes

The pack-specific tools cover ISTAT dataflows only. A hosted pack connection also lists shared Pipeworx tools, so its tool count is larger than the three tools described here. The gateway’s `initialize` response is the authoritative source for the tools available at connection time.

The local package does not include those shared gateway meta-tools. It uses the same source and pack tools but does not provide `ask_pipeworx` routing. Large unfiltered data requests can return substantial results, particularly when `get_data` is called without a key.

_Full upstream README: https://allmcps.com/mcp/istat-it/readme_