census-mcp-server

io.github.cyanheads/census-mcp-serverVersion 0.7.2

Query U.S. Census Bureau data, variables, and geography via MCP.

Status

Responds604 msNov 14, 2026, 14:48 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 14:48 UTC
Latency: 604 ms
Remotes responding: 1 of 1
Sign-in: No sign-in
Hosting: Hosted outside the EU (detected)
Registry data as of: Nov 14, 2026, 21:12 UTC

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Connect

Streamable HTTP

https://census.caseyjhand.com/mcpResponds604 msNov 14, 2026, 14:48 UTC

No sign-in

Claude Code

claude mcp add --transport http census-mcp-server https://census.caseyjhand.com/mcp

Claude Desktop and claude.ai

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Settings > Connectors > Add custom connector
Name: census-mcp-server
Remote MCP server URL: https://census.caseyjhand.com/mcp

Cursor

{
  "mcpServers": {
    "census-mcp-server": {
      "url": "https://census.caseyjhand.com/mcp"
    }
  }
}

VS Code

code --add-mcp '{"name":"census-mcp-server","type":"http","url":"https://census.caseyjhand.com/mcp"}'

Streamable HTTP

npm: @cyanheads/census-mcp-server 0.7.2

Package only

npm (npx)

claude mcp add census-mcp-server -- npx -y @cyanheads/census-mcp-server@0.7.2

Streamable HTTP

npm: @cyanheads/census-mcp-server 0.7.2

Package only

npm (npx)

claude mcp add census-mcp-server -- npx -y @cyanheads/census-mcp-server@0.7.2

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Tools

8 tools

Tools of census-mcp-server
	Description		Read-only	Idempotent	Open world
`census_compare_geographies`Compare one or more variables across multiple geographies at the same level — all counties in a state, all states nationally, or a named set of specific geographies — ranked on the value of one of them. Covers queries like "compare median income across WA counties" or "which states have the most people below the poverty line." A count ranks geographies by size, not by rate, so to rank a rate, rank a published percentage: S1701_C03_001E (percent below the poverty level, dataset acs/acs5/subject), DP03_0128PE (the same percentage, acs/acs5/profile), or DP04_0047PE (percent of occupied housing units that are renter-occupied, acs/acs5/profile). Profile and subject tables reach tracts but not block groups. Omit within to compare all geographies nationally at the level. Suppressed values are decoded to human-readable labels rather than passed through as raw negative sentinels. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, dec/ddhcb, and acs/acs1/spp, use predicates to rank within one industry, size class, or population group — a comparison that omits one ranks on a default the Census API picks, which is an all-categories total on some dimensions and a single category on others. Each row names the defaults that were applied in applied_filters, and census_list_predicate_values enumerates the codes a dimension accepts. Some dec/ddhca and dec/ddhcb tables split the population groups between them, publishing each group at a geography in only one table of the family, so a ranking on one of them leaves out the geographies whose group sits in a sibling table — the notice names those tables. A dataset that publishes several records per geography cannot be ranked until one is pinned: pep/charv publishes an April estimates base and a July estimate, so a comparison that pins neither fails with ambiguous_rows rather than giving every geography two ranks — pass predicates {"MONTH": "7"} for the July estimate.	Compare one or more variables across multiple geographies at the same level — all counties in a state, all states nationally, or a named set of specific geographies — ranked on the value of one of them. Covers queries like "compare median income across WA counties" or "which states have the most people below the poverty line." A count ranks geographies by size, not by rate, so to rank a rate, rank a published percentage: S1701_C03_001E (percent below the poverty level, dataset acs/acs5/subject), DP03_0128PE (the same percentage, acs/acs5/profile), or DP04_0047PE (percent of occupied housing units that are renter-occupied, acs/acs5/profile). Profile and subject tables reach tracts but not block groups. Omit within to compare all geographies nationally at the level. Suppressed values are decoded to human-readable labels rather than passed through as raw negative sentinels. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, dec/ddhcb, and acs/acs1/spp, use predicates to rank within one industry, size class, or population group — a comparison that omits one ranks on a default the Census API picks, which is an all-categories total on some dimensions and a single category on others. Each row names the defaults that were applied in applied_filters, and census_list_predicate_values enumerates the codes a dimension accepts. Some dec/ddhca and dec/ddhcb tables split the population groups between them, publishing each group at a geography in only one table of the family, so a ranking on one of them leaves out the geographies whose group sits in a sibling table — the notice names those tables. A dataset that publishes several records per geography cannot be ranked until one is pinned: pep/charv publishes an April estimates base and a July estimate, so a comparison that pins neither fails with ambiguous_rows rather than giving every geography two ranks — pass predicates {"MONTH": "7"} for the July estimate.	Not declared	Yes	Not declared	No
`census_get_variable`Fetch full metadata for one or more Census variable codes — label, concept group, predicate type, the table's universe, and margin-of-error sibling references. Use to confirm a variable code before building a query, or to look up what a known code means. On ACS datasets it returns estimate_code and moe_code sibling references so you can request both without a separate search, and a margin-of-error code carries attribute_of (its estimate) and attribute_type MARGIN_OF_ERROR; the ACS comparison profiles (acs/acs5/cprofile, acs/acs1/cprofile) and the other dataset families publish no margins of error and carry none of these fields. It also resolves the annotation and flag columns the data tools accept, such as B19013_001EA or EMP_F, naming the column each one belongs to, and predicate codes such as NAICS2017 or SEX, confirming a filter dimension exists in a dataset before a query uses it — for the values a dimension accepts rather than the dimension itself, call census_list_predicate_values.	Fetch full metadata for one or more Census variable codes — label, concept group, predicate type, the table's universe, and margin-of-error sibling references. Use to confirm a variable code before building a query, or to look up what a known code means. On ACS datasets it returns estimate_code and moe_code sibling references so you can request both without a separate search, and a margin-of-error code carries attribute_of (its estimate) and attribute_type MARGIN_OF_ERROR; the ACS comparison profiles (acs/acs5/cprofile, acs/acs1/cprofile) and the other dataset families publish no margins of error and carry none of these fields. It also resolves the annotation and flag columns the data tools accept, such as B19013_001EA or EMP_F, naming the column each one belongs to, and predicate codes such as NAICS2017 or SEX, confirming a filter dimension exists in a dataset before a query uses it — for the values a dimension accepts rather than the dimension itself, call census_list_predicate_values.	Not declared	Yes	Not declared	No
`census_list_datasets`Browse available Census Bureau datasets with their supported vintage years. Use as the starting point when the right dataset is unknown — ACS5, ACS1, and their profile, subject, and comparison tables, population estimates, the decennial census files, and the business datasets (County Business Patterns, Economic Census, Nonemployer Statistics) serve different use cases. Pass the dataset_id value to the dataset parameter in other census tools. Each description names the predicates a dataset requires and the geography levels it publishes, both of which vary by dataset.	Browse available Census Bureau datasets with their supported vintage years. Use as the starting point when the right dataset is unknown — ACS5, ACS1, and their profile, subject, and comparison tables, population estimates, the decennial census files, and the business datasets (County Business Patterns, Economic Census, Nonemployer Statistics) serve different use cases. Pass the dataset_id value to the dataset parameter in other census tools. Each description names the predicates a dataset requires and the geography levels it publishes, both of which vary by dataset.	Not declared	Yes	Not declared	No
`census_list_geographies`List the geography levels available for a given Census dataset and year, along with the parent geographies each level requires. Use before querying to confirm that the target geography level exists — ACS1 omits many sub-state levels, and not all datasets support tracts or block groups. The geography_level values returned here are the valid inputs to the geography_level parameter in census_query_data and census_compare_geographies.	List the geography levels available for a given Census dataset and year, along with the parent geographies each level requires. Use before querying to confirm that the target geography level exists — ACS1 omits many sub-state levels, and not all datasets support tracts or block groups. The geography_level values returned here are the valid inputs to the geography_level parameter in census_query_data and census_compare_geographies.	Not declared	Yes	Not declared	No
`census_list_predicate_values`List the codes a Census filter dimension accepts, so a predicates map can be written without guessing. Answers the question left open when census_query_data or census_compare_geographies reports that a dimension was left unset. Which route a dimension takes depends on the vintage: NAICS and POPGROUP always publish a value list in the dataset dictionary, and on the current vintages EMPSZES, LFO, RCPSZES, TAXSTAT, and TYPOP publish none and are enumerated here against the live data endpoint instead, which needs the server's Census API key. A dictionary value list is a classification shared across Census products rather than a list of what one dataset serves, and roughly half of its codes typically return no rows anywhere — those are checked against the dataset's own published rows and dropped, a check that also reads the data endpoint and so needs the key; without a working key the dictionary list comes back unchecked, and the response source field says whether that check ran. The dictionary lists run to thousands of codes and are best narrowed with query. Pass the returned code as the dimension's value in predicates.	List the codes a Census filter dimension accepts, so a predicates map can be written without guessing. Answers the question left open when census_query_data or census_compare_geographies reports that a dimension was left unset. Which route a dimension takes depends on the vintage: NAICS and POPGROUP always publish a value list in the dataset dictionary, and on the current vintages EMPSZES, LFO, RCPSZES, TAXSTAT, and TYPOP publish none and are enumerated here against the live data endpoint instead, which needs the server's Census API key. A dictionary value list is a classification shared across Census products rather than a list of what one dataset serves, and roughly half of its codes typically return no rows anywhere — those are checked against the dataset's own published rows and dropped, a check that also reads the data endpoint and so needs the key; without a working key the dictionary list comes back unchecked, and the response source field says whether that check ran. The dictionary lists run to thousands of codes and are best narrowed with query. Pass the returned code as the dimension's value in predicates.	Not declared	Yes	Not declared	No
`census_query_data`Query a Census dataset for one or more variables at one geography, a list of geographies at the same level, or every geography at a level. Accepts FIPS codes for the target geography — use census_resolve_geography to convert place names to FIPS when needed. On ACS datasets, labeled estimates and margin-of-error values are returned together (the comparison profiles publish no margins), and the negative sentinel values the Census writes for an estimate or margin of error it cannot publish are decoded into the meanings the Census gives them rather than passed through as raw numbers. A value cbp, ecnbasic, or nonemp withheld is stored as 0 beside a flag, and is reported as withheld, with the meaning of its flag, rather than as a zero. Pass geography_fips as "*" for every geography at the level within the parent, or as a comma-separated list of codes ("06,53") for several: rows come back in GEOID order, up to limit per call (default 50, max 500), with totalCount giving how many matched and offset reaching the rest — the order is not a ranking, so use census_compare_geographies to rank. The notice names any listed code that no row came back for. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, dec/ddhcb, and acs/acs1/spp, use predicates to filter by industry, size class, or population group — a query that omits one is answered with a default the Census API picks, which is an all-categories total on some dimensions and a single category on others. Each row names the defaults that were applied in applied_filters, and census_list_predicate_values enumerates the codes a dimension accepts. Some dec/ddhca and dec/ddhcb tables split the population groups between them, publishing each group at a geography in only one table of the family, so where a result can be missing a group, a geography, or a value, the notice names the sibling tables to look in. One geography can also come back on more than one row: pep/charv publishes an April estimates base alongside	Query a Census dataset for one or more variables at one geography, a list of geographies at the same level, or every geography at a level. Accepts FIPS codes for the target geography — use census_resolve_geography to convert place names to FIPS when needed. On ACS datasets, labeled estimates and margin-of-error values are returned together (the comparison profiles publish no margins), and the negative sentinel values the Census writes for an estimate or margin of error it cannot publish are decoded into the meanings the Census gives them rather than passed through as raw numbers. A value cbp, ecnbasic, or nonemp withheld is stored as 0 beside a flag, and is reported as withheld, with the meaning of its flag, rather than as a zero. Pass geography_fips as "*" for every geography at the level within the parent, or as a comma-separated list of codes ("06,53") for several: rows come back in GEOID order, up to limit per call (default 50, max 500), with totalCount giving how many matched and offset reaching the rest — the order is not a ranking, so use census_compare_geographies to rank. The notice names any listed code that no row came back for. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, dec/ddhcb, and acs/acs1/spp, use predicates to filter by industry, size class, or population group — a query that omits one is answered with a default the Census API picks, which is an all-categories total on some dimensions and a single category on others. Each row names the defaults that were applied in applied_filters, and census_list_predicate_values enumerates the codes a dimension accepts. Some dec/ddhca and dec/ddhcb tables split the population groups between them, publishing each group at a geography in only one table of the family, so where a result can be missing a group, a geography, or a value, the notice names the sibling tables to look in. One geography can also come back on more than one row: pep/charv publishes an April estimates base alongside	Not declared	Yes	Not declared	No
`census_resolve_geography`Resolve a place name, ZIP code, or street address to Census FIPS identifiers. Converts names like "King County, WA", "Seattle, WA", or "Seattle-Tacoma-Bellevue, WA", and ZIPs like "98109", to the codes required by census_query_data and census_compare_geographies. Use before querying when you have a place name rather than raw FIPS codes — state_fips maps to parent_fips and fips_summary maps to geography_fips in downstream tools, and geography_type is itself the geography_level to query at.	Resolve a place name, ZIP code, or street address to Census FIPS identifiers. Converts names like "King County, WA", "Seattle, WA", or "Seattle-Tacoma-Bellevue, WA", and ZIPs like "98109", to the codes required by census_query_data and census_compare_geographies. Use before querying when you have a place name rather than raw FIPS codes — state_fips maps to parent_fips and fips_summary maps to geography_fips in downstream tools, and geography_type is itself the geography_level to query at.	Not declared	Yes	Not declared	No
`census_search_variables`Search Census variables by keyword across variable labels and concept groups, or look one up by its code. Returns variable codes with human-readable labels — use this to go from a concept like "median household income" to the variable code B19013_001E needed for data queries. A query that is one variable or table code, such as B19013_001E or B19013, returns that variable or the table's variables, in code order, ahead of any keyword matches; a code the dataset does not publish gets a notice naming the dataset that does, when one is confirmed. On ACS datasets it returns both estimate (E suffix) and margin-of-error (M suffix) codes so you can request both; the ACS comparison profiles (acs/acs5/cprofile, acs/acs1/cprofile) and the other dataset families publish no margins of error. Also use it to find the predicate codes a dataset filters on, such as NAICS2017 in cbp. Adding a word narrows the results, since every word must match. Use offset to continue the same search beyond limit; nextOffset names the next page.	Search Census variables by keyword across variable labels and concept groups, or look one up by its code. Returns variable codes with human-readable labels — use this to go from a concept like "median household income" to the variable code B19013_001E needed for data queries. A query that is one variable or table code, such as B19013_001E or B19013, returns that variable or the table's variables, in code order, ahead of any keyword matches; a code the dataset does not publish gets a notice naming the dataset that does, when one is confirmed. On ACS datasets it returns both estimate (E suffix) and margin-of-error (M suffix) codes so you can request both; the ACS comparison profiles (acs/acs5/cprofile, acs/acs1/cprofile) and the other dataset families publish no margins of error. Also use it to find the predicate codes a dataset filters on, such as NAICS2017 in cbp. Adding a word narrows the results, since every word must match. Use offset to continue the same search beyond limit; nextOffset names the next page.	Not declared	Yes	Not declared	No

Details

Registry status: Active
Published: Nov 4, 2026
Updated: Nov 4, 2026
Website: Not given
Repository: https://github.com/cyanheads/census-mcp-server⁠ (opens in a new tab)
Categories (suggested): Data and analyticsSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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