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who-gho-mcp-server

Search WHO GHO Indicators

who_search_indicators
Read-onlyIdempotent

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", "mortality", "diabetes", or "HIV". If results are truncated, refine the query or page further into the same filtered result set with offset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of indicators to return. Default 20, max 100.
queryYesKeyword to search in indicator names, e.g. "life expectancy" or "tuberculosis".
offsetNoZero-based offset into the matches for this query. Default 0. Read hasMore and nextOffset from the response to continue paging. An offset at or beyond totalCount returns an empty indicators array, not an error.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
noticeNoPresent when matches were withheld or the requested offset ran past the end of the result set. Explains how to reach the remaining matches.
offsetNoZero-based offset this page started at.
hasMoreNoTrue when more matches remain beyond this page. Pair with nextOffset to continue.
pageInfoNoHuman-readable page position, e.g. "offset 0, showing 20 of 3003". Use to construct the next offset.
indicatorsNoMatching indicators up to the requested limit.
nextOffsetNoOffset to request for the next page. Absent when this page reached the end of the matches.
totalCountNoTotal indicators matching the query in the catalog, before the limit is applied.
effectiveQueryNoKeyword used for the catalog search, as received by the server.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, so the description correctly avoids repeating those. It adds meaningful behavior: substring match semantics, pagination via offset with hasMore/nextOffset, and the fact that an out-of-range offset returns an empty array rather than an error. This is rich disclosure beyond the structured annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the primary purpose, followed by usage examples and a pagination caveat. No redundant language, and every sentence adds useful context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with a full output schema (hasMore/nextOffset referenced), the description covers purpose, usage, matching behavior, pagination, and failure modes. An agent has everything needed to call it correctly without ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already documented. The description adds value by providing concrete example search terms (e.g., life expectancy, immunization) and clarifying offset behavior beyond the schema note (e.g., reading hasMore/nextOffset, empty result behavior). This goes beyond the baseline but does not fully rewrite parameter docs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (search), resource (WHO GHO indicator catalog), and criterion (keyword in indicator name). It differentiates from siblings like who_list_indicators by emphasizing the substring search and by explicitly linking the returned codes to who_query_indicator_data, making the tool's role clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: the tool is for finding indicator codes/names to pass to who_query_indicator_data. It offers example keywords and explains pagination refinement for truncated results. However, it does not explicitly contrast with sibling tools like who_list_indicators or when to prefer one over the other, so it stops short of a full when/when-not comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: browsing/searching indicators, fetching metadata, listing dimensions, listing dimension values, and querying data. There is minor overlap between listing and searching indicators, but the descriptions explicitly differentiate them (browse vs. keyword search), leaving no ambiguity.

Naming Consistency5/5

All tools follow the 'who_<verb>_<noun>' pattern (e.g., who_list_dimensions, who_query_indicator_data), with verbs like get, list, search, and query used consistently. The uniform prefix and structure create a predictable and coherent naming scheme.

Tool Count5/5

Six tools is an ideal size for this domain, covering the full WHO GHO workflow without redundancy. Each tool supports a distinct step in discovery and data retrieval, making the set well-scoped and efficient.

Completeness5/5

The tool set covers the entire necessary surface for working with WHO GHO data: discovering indicators (search/list), retrieving metadata, exploring dimensions and their values, and querying actual data with filters. No obvious gaps exist for a read-only health statistics API.