country-analytics-mcp
Related Servers
Alternatives to country-analytics-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables AI clients to ask quantitative questions about any continent's economy, answering with live reconciled GDP, population, per-capita, ranking, and historical FX conversion figures pulled from three public APIs at query time. Every judgment call—which countries count, how missing years are handled, which currency and FX date—is exposed as a parameter, and the server reports exactly which rows it excluded, why, and where each number came from.-
- AlicenseAqualityBmaintenanceEnables AI assistants to discover, retrieve, and compare official international development indicators from sources such as the World Bank, FAOSTAT, WHO, UNICEF, and IMF, while preserving source identifiers, units, and citations.101MIT

Thesma MCP Serverofficial
AlicenseAqualityDmaintenanceGives AI assistants access to SEC filings, BLS employment, Census demographics, and SBA lending data via natural language queries.60MIT- AlicenseNot gradedqualityDmaintenanceServer that brings World Bank Open Data to AI assistants. 10 tools · Zero authentication · LRU caching · Sparkline trends · Cross-country comparisons1MIT
- AlicenseAqualityCmaintenanceQuery 2,500+ verified public datasets (World Bank, IMF, Eurostat, OECD, WHO) from your AI agent. Search, analyze, and visualize data, and publish charts — with verified SEC + official source data.28430 npm2MIT
- FlicenseNot gradedqualityDmaintenanceExposes World Bank development data to AI agents via local CSV resources and live API tools, enabling queries about GDP, population, and other indicators.-
TDQS
Scored across 8 tools
Tools are mostly distinct: list_continents, list_countries, and get_country_metric target different granularities, while region_total and rank_countries differ by aggregation vs ranking. However, both region_total and rank_countries share identical scope/year/currency semantics and could be confused for aggregate queries, and get_country_metric is buried despite its importance.
All tool names follow a clear verb_noun pattern (list_continents, get_country_metric, region_total, convert_currency, describe_methodology). The only slight deviation is region_total and rank_countries which omit an explicit verb, but they remain readable and consistent within the set.
Eight tools is well-scoped for a country analytics server: listing entities, fetching metrics, aggregating, ranking, converting currency, and explaining reconciliation/methodology. Each tool earns its place without redundancy.
The surface covers the full lifecycle: discovery (continents, countries), retrieval (get_country_metric), aggregation (region_total), ranking (rank_countries), currency conversion, and transparency tools (list_reconciliation_issues, describe_methodology). No obvious gaps for the stated domain.