nl-opendata-mcp
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- AlicenseNot gradedqualityCmaintenanceEnables searching, viewing metadata, and querying tabular resources from Netherlands Open Data (data.overheid.nl) via CKAN.3 npm1MIT
- AlicenseNot gradedqualityBmaintenanceEnables language models to search and query Statistics Netherlands open data, turning natural-language questions into traceable statistics by discovering tables, resolving codes, and retrieving filtered observations.MIT
- AlicenseNot gradedqualityCmaintenanceProvides access to the Dutch national open-data portal (data.overheid.nl) via CKAN API, enabling listing organizations and datasets through direct tool calls or natural language queries.3 npm1MIT
- AlicenseBqualityDmaintenanceAn unofficial MCP server providing access to Dutch government open data from data.overheid.nl, CBS statistics, and KVK business registry. Enables natural language queries for discovering datasets, inspecting metadata, and querying data without API keys or authentication.14MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying Statistics Netherlands (CBS) data, including metadata for tables like '37296eng', through an MCP interface.3 npmMIT
- AlicenseBqualityNot gradedmaintenanceEnables AI assistants and CLI tools to explore and analyze datasets from 600+ global CKAN open-data portals. Provides comprehensive tools for dataset discovery, datastore queries, metadata analysis, and local downloads without writing custom CKAN integrations.14MIT
TDQS
Scored across 9 tools
Every tool serves a clearly distinct purpose: listing, searching, checking availability, estimating size, retrieving metadata, inspecting details, querying data, saving to file, and listing local files. There is no overlap or ambiguity.
All tools follow a consistent 'cbs_verb_noun' pattern in snake_case (e.g., cbs_list_datasets, cbs_query_dataset). The naming is predictable and well-structured.
With 9 tools covering discovery, metadata, querying, and local storage, the count is well-scoped for a data access server. Each tool is justified and the set feels neither sparse nor bloated.
The tool surface covers the full lifecycle of working with CBS datasets: discovery, metadata inspection, size estimation, querying with filtering, and saving locally. Minor gaps exist (e.g., no delete for local files, no direct download without saving), but these do not hinder core workflows.