ny-data-registry-mcp
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- FlicenseNot gradedqualityAmaintenanceEnables AI agents to turn natural-language questions into precise paths to authoritative primary data sources, recommending vetted government, international, and research datasets and providing step-by-step navigation instructions for locating and downloading the underlying data.-
- AlicenseNot gradedqualityBmaintenanceEnables querying NYC Open Data datasets using natural language, with tools to search datasets, run SoQL queries, and retrieve metadata, all without an API key.691 npmMIT
- AlicenseAqualityCmaintenanceEnables agents to discover and access Norwegian open government data by asking questions in natural language, performing filtered searches, running SPARQL queries, and downloading actual dataset files from publishers.6MIT
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Akil MCPofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to query NYC public records through a hosted MCP server, supporting civic workflows such as property research, business evaluation, public money tracking, and influence mapping.14 npmMIT- FlicenseNot gradedqualityAmaintenanceEnables AI agents and users to turn natural-language questions into precise paths to authoritative primary data sources, recommending the most relevant government, international organization, and research datasets with authority ratings, API details, and traceable evidence chains. It also provides step-by-step website navigation instructions for locating specific documents and data on complex official portals.-
TDQS
Scored across 9 tools
Most tools have clearly distinct roles: source discovery, place-level source lookup, query instructions, live checks, registry metadata, dataset search, column inspection, join discovery, and change tracking. The only meaningful overlap is find_sources versus list_sources_for_place when a place is used as a search term, but the descriptions clarify the difference between a general search and a comprehensive place profile.
The set mostly follows a consistent snake_case verb_noun convention: find_sources, list_sources_for_place, check_source, search_datasets, get_dataset_columns, find_joinable. Minor deviations are registry_info and whats_new, which are noun/phrase-style rather than verb_noun, but overall the naming remains predictable.
Nine tools is well-scoped for a registry/discovery server, with each tool covering a distinct part of the workflow: source discovery, place lookup, query guidance, health checks, registry metadata, dataset search, column inspection, joins, and change tracking. No tool feels redundant or missing from a count perspective.
The surface covers the core lifecycle well: finding sources, understanding how to query them, checking liveness, searching harvested datasets, inspecting columns, finding joinable datasets, and tracking changes. Minor gaps remain, such as a dedicated single-source detail tool beyond how_to_query or a direct dataset-detail lookup beyond column inspection, but agents can work around these.