# Health Statistics [Health: Active]

**Category:** 🧬 Biology & Bioinformatics  
**Repository:** https://github.com/ContentWriterco/Health-Statistics-MCP  
**GitHub Stars:** 0  
**Views:** 1  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/health-statistics

## Description
Health statistics for AI agents: life expectancy, causes of death, health spending, WHO data.

## Tools
Capabilities this server exposes over MCP:

- **search_catalog** — Find health datasets by topic, country and source.
- **inspect_dataset** — Check country coverage, dimensions and the latest values.
- **get_dataset** — Dataset metadata and period range.
- **get_series** — Time series for one country.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "health-statistics": {
    "url": "https://monit.ly/api/mcp/health"
  }
}
```

## Documentation

## What the Health Statistics MCP server does

Health Statistics MCP server gives AI agents access to health and population data from WHO, Eurostat, OECD, and the World Bank. Available subject areas include life expectancy, causes of death, health expenditure, healthcare resources, and broader population health measures.

The service is read-only. It is suited to research and comparison tasks such as comparing life expectancy between Japan and the EU average, reviewing health expenditure as a share of GDP, or checking hospital beds per 1,000 people in a country.

## How it works

The service is hosted remotely by Monitly and uses Streamable HTTP rather than a local process. Add this endpoint to an MCP-compatible client:

`https://monit.ly/api/mcp/health`

After connection, an agent can search the available catalog, examine a dataset's structure and coverage, retrieve metadata, or request a country-level time series. The service does not require an account or key for normal use. A fair-use daily limit applies; higher-volume access is available through the keyed Monitly MCP described in the linked documentation.

## Setup and configuration

For Claude, add a custom connector in Settings → Connectors → Add custom connector, then paste the endpoint URL. Cursor, VS Code, and Windsurf can use an `mcp.json` entry with the server URL:

```json
{
  "mcpServers": {
    "health-statistics": {
      "url": "https://monit.ly/api/mcp/health"
    }
  }
}
```

ChatGPT can connect through Settings → Apps → Developer mode → Create by pasting the same URL. Gemini CLI can install the repository as an extension with:

```bash
gemini extensions install https://github.com/ContentWriterco/Health-Statistics-MCP
```

Setup guides for Claude, ChatGPT, Gemini, Grok, Le Chat, Perplexity, Cursor, VS Code, and Claude Code are available at Monitly's MCP connection guide.

## Tools and capabilities

The Health Statistics MCP server exposes four tools:

- `search_catalog` finds datasets by topic, country, and source.
- `inspect_dataset` reports country coverage, dimensions, and the latest values.
- `get_dataset` returns dataset metadata and its available period range.
- `get_series` retrieves a time series for one country.

Together, these tools support dataset discovery before retrieval, basic inspection of available values, and focused country-level historical queries.

## Limitations and notes

Results are limited to the datasets exposed through the service and its listed source collections. The server does not provide write operations. Anonymous use has a fair-use daily limit, so recurring or high-volume workloads may require the keyed Monitly MCP. The provided endpoint is remote, which means client access depends on network connectivity.

The broader Monitly public MCP catalog covers more than health data and is separate from this focused endpoint.

_Full upstream README: https://allmcps.com/mcp/health-statistics/readme_