statsmapped-mcp
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FlicenseNot gradedqualityBmaintenanceEnables LLM agents to query the Explore Local Statistics API for local area data like employment rates and demographics.-- AlicenseAqualityBmaintenanceEnables AI agents to perform due diligence on Irish properties by querying public datasets for planning applications, sold prices, flood risk, radon risk, and zoning.141 npm7MIT
- AlicenseNot gradedqualityNot gradedmaintenanceEnables AI agents to query and retrieve public statistical data from Data Commons through search and observation tools. Provides access to demographic, economic, and other statistical indicators for analysis and research.Apache 2.0
- AlicenseAqualityDmaintenanceEnables access to official UK Office for National Statistics data including demographics, economics, and social statistics through the ONS Beta API. Supports browsing, searching, and querying datasets with built-in shortcuts for popular statistics like inflation, regional GDP, and wellbeing data.511 npmMIT
- AlicenseAqualityDmaintenanceEnables AI assistants to query UK property data including EPCs, sale history, planning, flood risk, council tax, demographics, and more via the Homedata API.18MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying statistical data from the Statistical Office of the Slovak Republic via natural language or direct tool calls.2 npmMIT
TDQS
Scored across 9 tools
Each tool targets a distinct resource/action: global dataset listing, area listing, per-area dataset listing, detailed dataset retrieval, ranking, comparison listing, comparison details, comparability check, and metric explanation. The descriptions explicitly call out differences (e.g., stat_key vs series_key, list_datasets vs list_area_datasets), eliminating ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case: list_datasets, list_areas, list_area_datasets, get_dataset_for_area, rank_areas, list_comparisons, get_comparison, check_comparability, explain_metric. No mixed conventions or vague verbs.
9 tools is well within the ideal 3-15 range. Each tool serves a distinct purpose in the domain of querying Irish/UK statistical data, and none feel redundant or unnecessary.
The tool set covers the full lifecycle of data exploration: discovery (list_datasets, list_areas, list_area_datasets, list_comparisons), retrieval (get_dataset_for_area, get_comparison), ranking, comparability checking, and metric explanation. There are no obvious gaps; even history and caveats are handled.