census-mcp-server

Quality 78 / 100good

8 tools, about 8,140 tokens to load them all · tool set f3c970588205 · tools last changed 2026-10-13 · checked 2026-10-19 10:20 UTC

Tool changes

• 2026-10-13census_compare_geographieschangeddescription, input schema, output schema
  before

  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, 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. 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.

  after · 92% of words in common

  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.

• 2026-10-13census_query_datachangeddescription, input schema, output schema
  before

  Query a Census dataset for one or more variables at a specific geography. 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: 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. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, 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. One geography can also come back on more than one row: pep/charv publishes an April estimates base alongside its July estimate, and each row carries a record field saying which it is.

  after · 91% of words in common

  Query a Census dataset for one or more variables at a specific geography. 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: 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. 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 its July estimate, and each row carries a record field saying which it is.

• 2026-10-13census_resolve_geographychangedinput schema, output schema
• 2026-10-13census_list_predicate_valueschangedinput schema, output schema
• 2026-10-13census_get_variablechangeddescription, output schema
  before

  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 and attribute_type MARGIN_OF_ERROR as the Census publishes them; 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.

  after · 97% of words in common

  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.

• 2026-10-13census_search_variableschangeddescription, input schema, output schema
  before

  Search Census variables by keyword across variable labels and concept groups. 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. 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; when totalMatches exceeds the limit, a more specific query reaches the rest.

  after · 78% of words in common

  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; when totalMatches exceeds the limit, a more specific query reaches the rest — except past the limit of a table code, where a later variable's own code does.

• 2026-10-13census_list_geographieschangedoutput schema
• 2026-09-25census_compare_geographieschangeddescription, input schema, output schema
  before

  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, and dec/ddhca, 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. 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.

  after · 99% of words in common

  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, 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. 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.

• 2026-09-25census_query_datachangeddescription, input schema, output schema
  before

  Query a Census dataset for one or more variables at a specific geography. 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, 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: 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. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, and dec/ddhca, 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. One geography can also come back on more than one row: pep/charv publishes an April estimates base alongside its July estimate, and each row carries a record field saying which it is.

  after · 96% of words in common

  Query a Census dataset for one or more variables at a specific geography. 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: 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. On the business datasets (cbp, ecnbasic, nonemp), pep/charv, dec/ddhca, 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. One geography can also come back on more than one row: pep/charv publishes an April estimates base alongside its July estimate, and each row carries a record field saying which it is.

• 2026-09-25census_resolve_geographychangeddescription, input schema, output schema
  before

  Resolve a place name or street address to Census FIPS identifiers. Converts names like "King County, WA", "Seattle, WA", or "Seattle-Tacoma-Bellevue, WA" 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.

  after · 93% of words in common

  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.

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Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.