# Unicef [Health: Active]

**Category:** 🧮 Data Science Tools  
**Repository:** https://github.com/pipeworx-io/mcp-unicef  
**GitHub Stars:** 0  
**npm Downloads (last month):** 796  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/unicef

## Description
UNICEF Data (UN Children's Fund) MCP — global statistics on child health,

## Tools
Capabilities this server exposes over MCP:

- **list_dataflows** — Browse or keyword-search UNICEF's datasets (dataflows). UNICEF Data covers child health, nutrition, education, child protection, child mortality, child poverty, immunization, water/sanitation/hygiene (WASH) and the child-related SDGs. Each result has an `id` (the dataflowId you pass to dataflow_str…
- **dataflow_structure** — Get the structure (Data Structure Definition) of one UNICEF dataset: its ordered dimensions and, for each, the valid codes (e.g. countries, indicators, sex, age, wealth quintile). Use this to learn how to build the dot-separated SDMX `key` for get_data. The key has one position per dimension, in `d…
- **get_data** — Pull observations from a UNICEF 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. Call dataflow_structure first to learn the dimension order and valid codes. Example: get_data({ datafl…

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

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

## Documentation

## What the Unicef MCP server does

The Unicef MCP server exposes UNICEF Data through three focused MCP tools. It supports discovery of roughly 70 UNICEF datasets, inspection of each dataset’s structure, and retrieval of observations. The available subject areas include child health, nutrition, education, child protection, child mortality, child poverty, immunization, water, sanitation and hygiene, and child-related Sustainable Development Goals.

This makes the server useful when an agent needs source data rather than general discussion. For example, an agent can find a mortality dataset, identify its country and indicator codes, then request the relevant time series.

## How it works

The tools follow a discovery-to-query sequence. First, call `list_dataflows`, optionally providing a keyword such as `mortality` or `nutrition`. Each result includes a dataflow ID, version, and English name.

Next, pass that ID to `dataflow_structure`. The response describes the dataset’s ordered dimensions and the valid codes within them, such as countries, indicators, sex, age, or wealth quintile. This order is required for the final query.

Finally, call `get_data` with the dataflow ID and a dot-separated SDMX key. Each key position corresponds to one dimension from `dataflow_structure`; an empty position acts as a wildcard. The response contains decoded series, dimension labels, and values for each period. Omitting the key or passing an empty value requests all series and may return a large result.

## Setup and configuration

The Unicef MCP server can be connected through the hosted endpoint `https://gateway.pipeworx.io/unicef/mcp`. The README provides configuration examples for Claude Desktop, Cursor, and Windsurf. The same gateway also exposes a full endpoint at `https://gateway.pipeworx.io/mcp`.

For local use, run the package with `npx -y @pipeworx/mcp-unicef` and configure the MCP client to start that command. The local process communicates over standard input and output and exposes only the UNICEF pack’s three tools. No Pipeworx account or gateway round-trip is required for this mode.

The tools can also be called over HTTP. For example, the gateway exposes `POST https://gateway.pipeworx.io/v1/tools/unicef_list_dataflows` with a JSON body containing an optional `query`.

## Tools and capabilities

- `list_dataflows`: Search or browse UNICEF dataflows.
- `dataflow_structure`: Inspect dimension order and valid codes for a selected dataflow.
- `get_data`: Retrieve observations using SDMX dimension filters and wildcards.
- Query topics including mortality, nutrition, education, immunization, WASH, and child-related SDGs.

## Limitations and notes

The Unicef MCP server requires the dimension order and valid codes before constructing reliable `get_data` keys. Broad requests can produce large responses. Hosted pack connections also include shared Pipeworx meta-tools in addition to the three UNICEF tools; the exact tool list is reported by the connection’s `initialize` response. The local package does not include those shared meta-tools. The project is licensed under MIT.

_Full upstream README: https://allmcps.com/mcp/unicef/readme_