census-mcp
Related Servers
Alternatives to census-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables location intelligence for US ZIP codes, allowing users to search, profile, and compare ZIP codes across various domains like crime, income, schools, and more.-
- FlicenseNot gradedqualityDmaintenanceEnables access to U.S. Census Bureau data including demographics, population, income, and housing statistics. Users can query specific variables, search datasets, and retrieve geographic FIPS codes across various surveys like the American Community Survey and Decennial Census.1-
- AlicenseAqualityBmaintenanceProvides IRS income and tax statistics by ZIP code, enabling LLM agents to query income distribution, tax liabilities, credits, and deductions for any U.S. ZIP code using public IRS SOI data without an API key.1032 PyPIMIT
- AlicenseNot gradedqualityBmaintenanceEnables ZIP and postal code lookups—resolving codes to city, state, and coordinates for 60+ countries, and fetching all postal codes for a city—via the Zippopotam.us API.23 npmMIT
- FlicenseNot gradedqualityAmaintenanceConnects AI assistants with official Census Bureau data sources, letting them list datasets, resolve place names to FIPS codes, and pull aggregate statistics for states, counties, cities, and other geographies. Queries are served from the Census Data API with a local Postgres mirror for faster, more robust search.-
- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to discover Census datasets, resolve geographies to FIPS codes, fetch aggregate statistics, and retrieve population data from official Census Bureau sources.-
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: validation, metric-specific lookups, comparison, reverse lookup, and raw ACS access. There is no overlap or ambiguity between them.
All tool names follow a consistent verb_noun snake_case pattern (lookup_zip, get_income, compare_zips, etc.). No mixed styles or vague verbs.
8 tools is well-scoped for a census data server. Each tool covers a meaningful aspect of the domain without bloat or redundancy.
The set covers core census data needs: validation, income, demographics, housing, education, comparison, reverse lookup, and raw variable access. Minor gaps like age-bracket breakdowns exist but are noted as roadmap, and the raw access tool mitigates many limitations.