Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GHED_MCP_CACHE_DIRNoDirectory to store the GHED cache (default: ~/.cache/ghed-mcp)

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
refresh_cacheA

Download or re-download the public GHED workbook and rebuild SQLite.

cache_statusA

Return cache status and WHO source-document details; initializes an empty cache.

The first call may take minutes. Run ghed-mcp --warm-cache in a terminal first if the MCP client has a short tool timeout. Use check_for_updates to check for newer WHO data without downloading the workbook.

check_for_updatesA

Compare the local cache source document with the current GHED all-data file.

versionA

Return workbook version lines and cache provenance.

methodology_guideA

Explain how GHED variables are organized and how to choose the right series.

topics_indexA

Curated GHED topic index mapping common user requests to variable codes.

research_use_casesB

Research patterns seen in GHED-using literature, with recommended variables.

suggest_variables_for_research_questionA

Map a natural-language research question to likely GHED variables and cautions.

list_variable_categoriesA

List GHED variable category counts from the Codebook.

list_indicatorsB

List headline GHED indicators only (category_1 = INDICATORS).

list_variablesC

List all GHED Codebook variables, optionally filtered by category.

search_indicatorsA

Search headline indicators; use search_variables for detailed SHA series.

This is substring search, not semantic search. Use a short fragment such as 'out-of-pocket', 'GGE' or 'che_gdp', not a full research question. If no match, shorten the query or use topics_index. category_1=None searches all variables.

search_variablesA

Search all Codebook variables; use search_indicators for headline measures.

This is substring search. Use a short code/name fragment, not a full question. An empty result can mean the wording did not match; shorten the query or use topics_index before concluding that a variable is unavailable.

list_countriesA

List countries and territories available in GHED, optionally by group.

country_group accepts curated codes (LAC, OECD, LDC, SSA, …) and intersects with region / income when more than one is set, so country_group="LAC", income="High" returns LAC HICs.

list_country_groupsB

List GHED country grouping values by region and World Bank income class.

list_curated_country_groupsA

List Decilion's curated country groupings (WB regions, LDCs, OECD).

Returns groups beyond GHED's built-in WHO regions and World Bank income classes — World Bank geographic regions, the UN Least Developed Countries list, and OECD membership. Use the returned members lists with the countries parameter on data tools, or pass the group code to resolve_country_group_membership to get just the ISO3 list.

resolve_country_group_membershipA

Resolve a curated group code to its ISO3 member list.

Accepts canonical codes (LAC, SSA, LDC, OECD, …), official WB region codes (LCN, SSF, …), and common spellings ("Latin America and Caribbean", "Sub-Saharan Africa", "Least Developed Countries").

find_country_codeC

Find ISO3 country codes by name, alias, or code fragment.

get_indicator_metadataB

Return Codebook metadata for one GHED indicator.

get_country_metadataA

Return source, data-type and estimation notes from the Metadata sheet.

If no indicator-specific notes exist, query country alone for broader notes. Country notes are context, not proof of the selected indicator's data type or the cause of a trend. Empty metadata does not establish data quality.

data_availabilityA

Summarize availability for indicators before building a research panel.

additive_hierarchyB

Return known additive child relationships for a GHED variable.

explain_indicator_relationshipB

Explain whether a variable is a total, component, ratio/share, or context series.

build_additive_breakdownB

Check a current-NCU accounting total for one country-year.

Use additive_hierarchy to choose a relationship. If complete is false, the identity cannot be validated even when observed components nearly sum to the total. Missing components are not zero or implicitly included elsewhere.

build_research_panelA

Build a tidy long panel for multiple GHED variables across countries and years.

country_group accepts curated codes ("LAC", "OECD", "LDC", "SSA", …) that resolve to ISO3 lists; combine freely with countries, region, and income (filters apply via SQL AND).

build_research_packageB

Build export-ready CSV data, codebook, and README text for a research extract.

get_indicator_dataA

Fetch one GHED indicator with optional country and year filters.

Spatial filters compose: country (singular), countries (list), and country_group (curated, e.g. "LAC") merge into a single country list, and region / income further constrain via SQL AND.

compare_countriesA

One GHED indicator across countries, returned as tidy rows or CSV.

Pass either an explicit countries list or a curated country_group (e.g. "LAC", "OECD", "LDC", "SSA") — or both, in which case they are merged. See list_curated_country_groups for available groups.

compare_country_groupA

Compare one GHED indicator across a country group (curated, regional, or income-based).

Pass at least one of country_group (e.g. "LAC", "OECD", "LDC"), region, or income. Multiple filters compose via SQL AND, so country_group="LAC", income="High" returns LAC HICs.

summarize_country_groupB

Summarize an indicator within a country group (curated, regional, or income).

Pass at least one of country_group ("LAC", "OECD", "LDC", …), region, or income.

indicator_trendA

Compute first/latest trends for one indicator; use compare_trends for several.

percent_change and cagr are fractions (0.10 = 10%). absolute_change is in the indicator's units, or percentage points for shares. Inspect actual first/latest years and change_units before interpreting or ranking results.

compare_trendsA

Compute first/latest summaries for several indicators; use indicator_trend for one.

percent_change and cagr are fractions (0.10 = 10%); absolute changes in shares are percentage points. Check each item's years, warnings and limits.

rank_country_changesA

Rank countries by change; use indicator_trend for unranked summaries.

metric='percent_change' and 'cagr' use fractions (0.10 = 10%), not percentage units. 'absolute_change' uses percentage points for shares, otherwise the indicator's original units. Compare actual first/latest years and change_units.

assess_data_qualityC

Summarize metadata, availability, and cautions for an indicator/filter.

country_profileB

Latest headline health-expenditure values for one country.

Prompts

Interactive templates invoked by user choice

NameDescription
compare_health_expenditureGuided prompt for comparative health-expenditure analysis.

Resources

Contextual data attached and managed by the client

NameDescription
methodology_resourceReadable methodology guide for GHED variable selection.

TDQS

B3.2/5.0

Scored across 35 tools

Disambiguation2/5

Multiple tools have heavily overlapping boundaries: compare_countries, compare_country_group, summarize_country_group, and get_indicator_data all retrieve one indicator across country sets, and compare_countries also accepts country_group, making the distinction unclear. Search and list tools similarly overlap across indicators vs. variables, and data quality/metadata tools are hard to separate without deep inspection.

Naming Consistency3/5

The set mostly uses verb_noun names like list_variables, get_indicator_data, and build_research_panel, but a substantial minority are noun-only commands such as country_profile, version, methodology_guide, topics_index, indicator_trend, and cache_status. The conventions are mixed but still readable and not chaotic.

Tool Count2/5

At 35 tools, the server is well beyond the 25+ threshold and feels over-granular for its domain. Several tools could be consolidated, especially the country-comparison trio and the search/list variants, without losing real capability.

Completeness5/5

The tool surface is unusually complete for the GHED domain: it covers discovery, metadata, data availability, country and group resolution, single-indicator retrieval, cross-country comparison, trend analysis, research panel construction, export packaging, and cache/version management. There are no obvious dead ends or missing operations for a read-only database server.

Maintenance

ActivityMaintained
ResponsivenessNo issues