Who Gho MCP Server

Last 30 days

Uptime

100%

Response time

262 ms typical, 262 ms slowest 5%

Last check

5 h ago

Next check

in 28 min

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "who-gho-mcp-server": {
      "type": "http",
      "url": "https://who-gho.caseyjhand.com/mcp"
    }
  }
}

6 tools

• who_list_dimensions

  List all dimension type codes and human-readable titles available in the WHO Global Health Observatory API. Use this to discover valid dimension codes before calling who_list_dimension_values. Common dimensions include COUNTRY, REGION, SEX, WORLDBANKINCOMEGROUP, and AGEGROUP, but

• who_list_dimension_values

  List valid codes and labels for a WHO GHO dimension type such as COUNTRY, REGION, SEX, WORLDBANKINCOMEGROUP, or AGEGROUP. Use this to discover valid filter values before calling who_query_indicator_data, or to confirm the correct ISO code for a country. Use who_list_dimensions to

• who_search_indicators

  Search the WHO Global Health Observatory indicator catalog by keyword in the indicator name. Returns indicator codes and names for use with who_query_indicator_data. The search uses a substring match on indicator names — try terms like "life expectancy", "immunization", "mortalit

• who_list_indicators

  Browse the WHO Global Health Observatory indicator catalog with pagination. Use when you want to explore indicators without a keyword, or to page through the full catalog. Use who_search_indicators when you have a keyword to narrow the results.

• who_get_indicator_metadata

  Fetch metadata for one or more WHO GHO indicator codes: the full indicator name and the dimensions it supports (e.g. COUNTRY, REGION, SEX, YEAR, WORLDBANKINCOMEGROUP, AGEGROUP). Call this before querying data with who_query_indicator_data to confirm which filter dimensions are va

• who_query_indicator_data

  Query data rows for a single WHO GHO indicator with optional spatial, temporal, and dimension filters. Returns rows with numeric values, uncertainty intervals (Low/High), and spatial/time metadata. This is the primary data-fetching tool in the find-then-query workflow: use who_se

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