ew-mcp
OfficialRelated Servers
Alternatives to ew-mcp
No user-submitted related servers found.
Related Servers
AlicenseNot gradedqualityCmaintenanceEnables querying the Urban Institute's Education Data Portal — harmonized federal data on schools, school districts, and colleges — through a discovery-first set of tools that search and describe datasets, fetch raw records or aggregated statistics, decode coded values, and resolve institution names to IDs, with no API key required and read-only access to the live API.MIT- AlicenseNot gradedqualityCmaintenanceFederated MCP server that routes K-12 education data requests to public sources like Urban Institute, EDC/Zelma, NAEP, and MA E2C, handling comparability and provenance automatically.MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying Sweden's municipal and regional key-performance-indicator (KPI) database, providing access to a wide range of public sector metrics via natural language.1MIT
- FlicenseNot gradedqualityDmaintenanceProvides access to over 800,000 economic time series from the Federal Reserve Bank of St. Louis, including data on GDP, inflation, and employment. It enables users to search for, retrieve, and analyze various economic indicators and state-level statistics.1-
- AlicenseCqualityDmaintenanceProvides access to Urban Institute's Education Data API through Claude, enabling users to query and analyze detailed educational data from schools, districts, and universities.22MIT
- AlicenseAqualityCmaintenanceProvides curated US economic data from Treasury, FRED, BLS, BEA, and other sources through an MCP interface. Enables querying economic series, fetching data with provenance tracking, and accessing cached artifacts.9MIT
TDQS
Scored across 4 tools
The four tools form a clear pipeline: search finds metrics by concept, describe explains a specific metric/indicator/essential question, resolve_place turns a name into a geoid, and get_data fetches values. There is mild overlap between search and describe (both surface framework content), but the args and outputs make the boundary clear in practice.
Two tools use bare verbs (search, describe) while two use a verb_noun pattern (resolve_place, get_data). Individually readable and unambiguous, but the conventions are mixed rather than a single predictable pattern.
Four tools is a tight, well-scoped read-only set for a data framework: discover, explain, geocode, fetch. Nothing feels redundant, though it sits near the thin end where one more operation (e.g. an explicit metric enumeration) might round it out.
The surface covers the full read lifecycle for the domain — find a metric, understand it, resolve a place, retrieve or rank values, including automatic benchmarks and disaggregation options. Being a read-only data server, missing write ops are not gaps; the main absence is a direct way to enumerate all available metrics/geographies without a query.