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Evidence row 1771344
Observed , by probe.mcp/1.
- Kind
- mcp.tools
- About
- endpoint 4c1c4905-c410-4c33-a30e-375bbbf46947
- Recorded
- Previous row
- #579719
- Body SHA-256
- 50a5a5b67930efd539b11c073fb5c4ada93d21edcebeb8fd659b898358888898
- Leaf
- 0xc128e3d49d0f60269eeb65496c91f5137b4da50a0c23d3dcd0dd44c756690201
What was observed
{
"count": 5,
"tools": [
{
"description": "Search the CDC dataset catalog by keyword, category, tag, or asset type. Returns IDs, names, truncated descriptions, asset types, column counts, update timestamps, and portal links. The catalog also holds charts, maps, stories, files, and links; an entry whose columnCount is 0 is one of those and yields no data from the other tools — reach a file or link through its permalink or accessPoints, and a chart or map through the dataset its parentIds name. Use cdc_get_dataset_schema for the full column list of a chosen dataset.",
"inputSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false,
"properties": {
"asset_types": {
"description": "Limit the search to these catalog asset types, spelled as assetType reports them. An entry matches when it is any one of them, and totalCount counts only those; [\"dataset\", \"filter\"] returns just the entries with rows to query. Omitted or [] searches every type.",
"items": {
"enum": [
"dataset",
"filter",
"chart",
"map",
"story",
"file",
"href"
],
"type": "string"
},
"type": "array"
},
"category": {
"description": "Filter by domain category (e.g., \"NNDSS\", \"Vaccinations\", \"Behavioral Risk Factors\"). Values come from the catalog's own vocabulary and are matched exactly, ignoring case — \"Vaccinations\" and \"vaccinations\" each match 89 entries while \"Vaccination\" matches none. Call cdc_list_catalog_vocabulary for every value with its entry count rather than guessing at one.",
"type": "string"
},
"domain": {
"default": "data.cdc.gov",
"description": "CDC Socrata host to search. \"data.cdc.gov\" (default) and \"chronicdata.cdc.gov\" front the same catalog and return the same entries, so switching hosts neither widens nor narrows a search — chronic-disease and small-area collections such as PLACES, the Heart Disease & Stroke Atlas, and Environmental Public Health Tracking are found from either.",
"enum": [
"data.cdc.gov",
"chronicdata.cdc.gov"
],
"type": "string"
},
"limit": {
"default": 10,
"description": "Results to return (default 10, max 10,000). offset plus limit must not exceed 10000.",
"maximum": 10000,
"minimum": 1,
"type": "integer"
},
"offset": {
"default": 0,
"description": "Pagination offset for browsing beyond first page (max 9999). offset plus limit must not exceed 10000; both CDC portals hold well under two thousand entries, so offsets near that ceiling page past the end of the catalog.",
"maximum": 9999,
"minimum": 0,
"type": "integer"
},
"order": {
"description": "Result ordering. Defaults to \"relevance\" when query is set and to \"dataset_id\" otherwise, at every offset; an explicit value always wins. \"relevance\" ranks the best matches for the query first, but its order varies between calls, so paging a relevance search by offset can repeat or skip entries. \"dataset_id\" sorts by each entry's catalog ID — a stable order whose offset pages walk every match exactly once.",
"enum": [
"dataset_id",
"relevance"
],
"type": "string"
},
"query": {
"description": "Full-text search across dataset names and descriptions (e.g., \"diabetes mortality\", \"lead exposure children\").",
"type": "string"
},
"tags": {
"description": "Filter by domain tags (e.g., [\"covid19\", \"surveillance\"]). Tags widen the search instead of narrowing it — a dataset matches when it carries any one of them, so every tag added returns more results, and an unrecognized tag matches nothing and leaves the result set unchanged. Values match the catalog's own tag vocabulary, case-insensitively; call cdc_list_catalog_vocabulary for the values in use with their entry counts, or read the tags field on any result. To narrow, combine tags with query or category, which intersect with the tag set.",
"items": {
"description": "Tag value",
"type": "string"
},
"type": "array"
}
},
"type": "object"
},
"name": "cdc_discover_datasets"
},
{
"description": "Fetch the column schema for a CDC dataset — names, data types, descriptions, row count, last-updated timestamp, and, for a filter, the dataset it is a view of — with the period and area it covers, how often it is updated, its suggested citation, license, and attribution wherever the publisher recorded them. A chart or map has no schema of its own; the failure names the dataset it is built on. Returns the first 100 columns by default; wide datasets continue via column_offset. The dataset description is capped at 4,000 characters by default; pass full_description: true for the whole text. Get dataset IDs from cdc_discover_datasets.",
"inputSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false,
"properties": {
"column_limit": {
"default": 100,
"description": "Columns to return in this call (default 100). Every dataset under the default arrives whole; past it the response reports totalCount and a nextOffset to pass back as column_offset. Raise this to pull a wide schema in one call — a value at or above the column count returns every column.",
"maximum": 9007199254740991,
"minimum": 1,
"type": "integer"
},
"column_offset": {
"default": 0,
"description": "Index of the first column to return, for continuing past a previous call (default 0). Columns keep the order the dataset declares, so column_offset plus column_limit walks the schema without gaps or repeats. An offset at or past the column count returns an empty window rather than an error.",
"maximum": 10000,
"minimum": 0,
"type": "integer"
},
"datasetId": {
"description": "Four-by-four dataset identifier (e.g., \"bi63-dtpu\"). Obtain from cdc_discover_datasets.",
"pattern": "^[a-z0-9]{4}-[a-z0-9]{4}$",
"type": "string"
},
"domain": {
"default": "data.cdc.gov",
"description": "CDC Socrata host to fetch the dataset from. \"data.cdc.gov\" (default) and \"chronicdata.cdc.gov\" front the same catalog, so a four-by-four ID resolves on either and the default works whichever host the dataset was found on.",
"enum": [
"data.cdc.gov",
"chronicdata.cdc.gov"
],
"type": "string"
},
"full_description": {
"default": false,
"description": "Return the dataset description whole (default false). By default a description longer than 4,000 characters is cut there, and the response sets descriptionTruncated and descriptionLength. Column descriptions are never shortened either way.",
"type": "boolean"
}
},
"required": [
"datasetId"
],
"type": "object"
},
"name": "cdc_get_dataset_schema"
},
{
"description": "List the controlled vocabularies cdc_discover_datasets' category and tags filters are matched against — every domain category and domain tag the CDC catalog publishes, each with the number of entries carrying it. Call it before filtering a search: a value the catalog does not carry matches nothing and returns an empty page, which is indistinguishable from a real value with no results. All categories come back whole; the tag vocabulary runs to roughly 1,600 values, so tags are ranked by entry count and returned one page at a time via tag_limit and tag_offset. Pass filter to narrow both vocabularies to the values whose words contain its words, or that appear whole inside it; a filter under three letters or digits matches whole words only.",
"inputSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false,
"properties": {
"domain": {
"default": "data.cdc.gov",
"description": "CDC Socrata host to read the vocabulary from. \"data.cdc.gov\" (default) and \"chronicdata.cdc.gov\" front the same catalog and publish the same vocabulary, so this selects which host answers, never which values exist.",
"enum": [
"data.cdc.gov",
"chronicdata.cdc.gov"
],
"type": "string"
},
"filter": {
"description": "Narrow both vocabularies to the values related to this text (at most 500 characters). A value matches when every word of the filter appears inside one of its words (\"vaccin\" reaches \"Vaccinations\" and \"covid-19 vaccination\"), or when the whole value appears in the filter. Matching is not fuzzy — a misspelling returns nothing rather than a guess. A word under three letters or digits matches only an equal word, so a short filter reaches the values carrying it as a whole word (\"tb\" reaches \"tuberculosis (tb)\", never \"outbreak\"); a short filter that reaches none, or one with no letters or digits, is ignored and both vocabularies come back unfiltered.",
"maxLength": 500,
"type": "string"
},
"tag_limit": {
"default": 50,
"description": "Tags to return in this call (default 50). Tags are ranked by entry count, so the default page is the most-used end of the vocabulary; the response reports how many matched and a nextOffset while more remain. A tag_limit at or above the number of matching tags returns all of them in one call. Categories are never paged — every one arrives whole.",
"maximum": 9007199254740991,
"minimum": 1,
"type": "integer"
},
"tag_offset": {
"default": 0,
"description": "Index of the first tag to return, for continuing past a previous call (default 0). Ranking is stable, so tag_offset plus tag_limit walks the vocabulary without gaps or repeats. An offset at or past the number of matching tags returns an empty tag list rather than an error.",
"maximum": 10000,
"minimum": 0,
"type": "integer"
}
},
"type": "object"
},
"name": "cdc_list_catalog_vocabulary"
},
{
"description": "Execute a SoQL query against any CDC dataset. Supports filtering, aggregation, sorting, full-text search, and field selection. Use cdc_discover_datasets to find dataset IDs and cdc_get_dataset_schema to inspect columns before querying.",
"inputSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false,
"properties": {
"datasetId": {
"description": "Four-by-four dataset identifier (e.g., \"bi63-dtpu\"). Obtain from cdc_discover_datasets.",
"pattern": "^[a-z0-9]{4}-[a-z0-9]{4}$",
"type": "string"
},
"domain": {
"default": "data.cdc.gov",
"description": "CDC Socrata host to query. \"data.cdc.gov\" (default) and \"chronicdata.cdc.gov\" front the same catalog, so a four-by-four ID returns the same rows from either and the default works whichever host the dataset was found on.",
"enum": [
"data.cdc.gov",
"chronicdata.cdc.gov"
],
"type": "string"
},
"group": {
"description": "SoQL GROUP BY clause. Requires aggregate functions in select.",
"type": "string"
},
"having": {
"description": "SoQL HAVING clause. Filters aggregated results.",
"type": "string"
},
"limit": {
"default": 100,
"description": "Rows to return (default 100). One call returns at most 1,000 rows: a larger limit, up to 1,000,000, is capped at 1,000, and the response says so and gives a nextOffset when more rows remain. Up to that cap, a page comes back shorter than limit only at the end of the result set.",
"maximum": 1000000,
"minimum": 1,
"type": "integer"
},
"offset": {
"default": 0,
"description": "Row offset for pagination (max 1,000,000). Pair with a deterministic order clause — an offset walk over unordered results can skip or repeat rows.",
"maximum": 1000000,
"minimum": 0,
"type": "integer"
},
"order": {
"description": "SoQL ORDER BY clause. Field name with optional ASC/DESC: \"total_deaths DESC\". Set one from the first page whenever paging with offset, and keep it for the whole walk: SODA does not order results implicitly, so consecutive offsets without a deterministic order, or under a changed one, can skip or repeat rows. End it with a tie-breaker unique to each row: on ungrouped rows, the system field `:id`, present on every dataset (order=\"year DESC, :id\"); on a grouped query, the grouped columns (order=\"total DESC, state\"); on a distinct select, the selected columns. Socrata rejects `:id` once rows are grouped.",
"type": "string"
},
"search": {
"description": "Full-text search across all text columns. For precise filtering use the where parameter instead.",
"type": "string"
},
"select": {
"description": "SoQL SELECT clause — column names, aliases, or aggregates: \"state, sum(deaths) as total_deaths\". Omit for all columns. To enumerate distinct values of a column, set select to \"{column}, count(*) as count\" with group=\"{column}\" and order=\"count DESC, {column}\".",
"type": "string"
},
"where": {
"description": "SoQL WHERE clause. Strings must be single-quoted: \"state='California' AND year=2020\". If a column name matches a SoQL keyword (group, select, where, order, limit, offset, having, search), wrap it in backticks: \"`group`='By Year'\".",
"type": "string"
}
},
"required": [
"datasetId"
],
"type": "object"
},
"name": "cdc_query_dataset"
},
{
"description": "Query CDC WONDER for national US mortality statistics — deaths, population, and crude/age-adjusted death rates — across its five mortality databases, selected with the database input: final underlying-cause data for 1999–2020 (the default) or 2018–2024, provisional data running from 2018 through the current year (its latest year partial, with a notice saying so), and two multiple-cause databases covering the same two eras. Break results out by year, month, age group, sex, race, Hispanic origin, or underlying cause of death — ICD-10 chapter or sub-chapter, CDC's 113-cause list, its 15 leading causes, or injury intent — and filter by ICD-10 cause of death, sex, age group, or year range; on a multiple-cause database, mcd_icd10 additionally matches a cause listed anywhere on the death certificate rather than only the one certified as underlying. Each database holds a different span of years (1999–2026 across all of them) and a request whose year_range falls outside the selected one's span is rejected with that span named. WONDER is a separate CDC system from the Socrata datasets the other cdc_* tools query. Data is national only — sub-national (state/county) breakdowns are not available through the API (CDC vital-statistics policy). Chapter and sub-chapter rows carry their ICD-10 code range as cause_code, which cause_icd10 accepts as it stands; 113-cause-list rows carry cause_level, their depth in that nested list, whose deeper causes are already counted in the cause containing them; leading_causes ranks the 15 leading causes by deaths and combines with no other grouping, while the filters still apply; month rows carry deaths only — CDC publishes no monthly population, so population and both rates come back \"Not Applicable\". The values each grouping dimension can take multiply to bound the table — year beside month, or icd_chapter beside icd_subchapter, adds nothing, since the finer level already enumerates the coarser — and a grouping that could produce more than 10,000 rows is refused before any request with the product named, since WONDER takes longer than the request deadline to answer a table that large; narrow year_range, sex or age_groups, or drop a dimension. Some measure cells come back as a CDC status token rather than a number — \"Suppressed\" (withheld for confidentiality), \"Unreliable\" (a rate CDC judges statistically unstable and does not show — on D76 and D77 when it is computed from 20 or fewer deaths, and D176, D158, and D157 when its 95% confidence interval is wider than 160% of the rate, whatever the death count), or \"Not Applicable\" (no population denominator); those cells read null in rows and each one is listed in cellNotes with its token. Each rate comes with the 95% confidence interval CDC publishes for it, as <rate>_lower and <rate>_upper right after the rate — null where CDC published none — so two rates can be compared by their intervals rather than their point values. CDC also drops whole rows before sending the table — strata with zero deaths, and strata whose death count is suppressed — so a stratum can be missing from rows entirely; messages carries CDC's statement whenever that happened. One call returns at most 10,000 rows: with limit omitted it returns the rest of the table up to that ceiling, a larger limit is lowered to it, and a smaller limit takes smaller pages; a page that stops short of the end reports the table's totalCount and a nextOffset to continue from. Paging shapes the response only — every call fetches the whole table from WONDER and returns a slice of it, so the figures, caveats and hidden-row notices are the same on every page and a smaller page saves no time. CDC rejects requests made less than 15 seconds apart across all five databases, so calls are spaced automatically: calls made while another is running wait their turn and run one after another, each queued call adding about 16 seconds plus its own query time before it returns. A request WONDER has not finished answering within 20 seconds fails as a retryable upstream_error, so one call queued behind another returns within about 56 seconds.",
"inputSchema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"additionalProperties": false,
"properties": {
"age_groups": {
"description": "Restrict to deaths in any of the listed age groups — e.g. [\"25-34\",\"35-44\"] covers both; a repeated group counts once. \"1\" is the under-1-year group. \"NS\" is the group CDC puts a death in when the age was not recorded; it is not covered by any of the ten-year groups, so a filter listing all eleven of those still leaves those deaths out and returns fewer deaths than the same query unfiltered. CDC refuses \"NS\" beside only some of the other groups: list it on its own to count those deaths, or list all twelve values — the same as omitting age_groups — to include them. Omit for all ages, which includes them.",
"items": {
"enum": [
"1",
"1-4",
"5-14",
"15-24",
"25-34",
"35-44",
"45-54",
"55-64",
"65-74",
"75-84",
"85+",
"NS"
],
"type": "string"
},
"type": "array"
},
"cause_icd10": {
"anyOf": [
{
"const": "",
"type": "string"
},
{
"enum": [
"999--999",
"999-999"
],
"type": "string"
},
{
"description": "ICD-10 underlying-cause code or range. WONDER takes a node of its ICD-10 tree — a chapter such as \"A00-B99\" (infectious) or \"V01-Y89\" (external causes), a block such as \"X40-X49\" (accidental poisoning) or \"C00-C97\" (malignant neoplasms), or a single code such as \"I21\" — and rejects any other span, e.g. \"X40-X44\", naming it in the error. List the codes (or blocks) to cover a span that is not a tree node.",
"pattern": "^[A-Z][0-9]{2}(\\.[0-9]+)?(-[A-Z][0-9]{2}(\\.[0-9]+)?)?$",
"type": "string"
},
{
"description": "A list of up to 50 entries, each in the single-value form, matched as a union: a death counts once when it matches any of them, so a code set such as X40–X44 plus X60–X64 is one series with one set of rates. Repeated entries are ignored. An empty list reads as omitted.",
"items": {
"anyOf": [
{
"enum": [
"999--999",
"999-999"
],
"type": "string"
},
{
"description": "ICD-10 underlying-cause code or range. WONDER takes a node of its ICD-10 tree — a chapter such as \"A00-B99\" (infectious) or \"V01-Y89\" (external causes), a block such as \"X40-X49\" (accidental poisoning) or \"C00-C97\" (malignant neoplasms), or a single code such as \"I21\" — and rejects any other span, e.g. \"X40-X44\", naming it in the error. List the codes (or blocks) to cover a span that is not a tree node.",
"pattern": "^[A-Z][0-9]{2}(\\.[0-9]+)?(-[A-Z][0-9]{2}(\\.[0-9]+)?)?$",
"type": "string"
}
],
"description": "One list entry: an ICD-10 code or range, or the withheld-cause marker."
},
"maxItems": 50,
"type": "array"
}
],
"description": "Filter to ICD-10 underlying causes of death — the single condition CDC certified as having started the chain of events leading to death. Takes one code or range, or a list of them for a cause defined as a code set, e.g. drug overdose as [\"X40\",\"X41\",\"X42\",\"X43\",\"X44\",\"X60\",\"X61\",\"X62\",\"X63\",\"X64\",\"X85\",\"Y10\",\"Y11\",\"Y12\",\"Y13\",\"Y14\"]. Omit for all causes. Accepted by every database. \"999--999\" is not an ICD-10 code but CDC's own marker for deaths whose cause it is still withholding under the provisional database's six-month reporting lag; it counts that backlog, and only the \"provisional\" database offers it. \"999-999\", the cause_code a sub-chapter row carries for the same deaths, is accepted too and sent as \"999--999\". On that database CDC withholds external-cause (V01-Y89) and sudden-death (R95, R96) causes for the 24 weeks before its data-through date, so a filter reaching them — a block or chapter containing one included — undercounts those weeks; the notice names the cutoff."
},
"database": {
"default": "underlying_1999_2020",
"description": "Which WONDER mortality database to query. \"underlying_1999_2020\" (D76) is final data for 1999–2020 and the default. \"provisional\" (D176) runs 2018 through the current year, updated weekly, and returns the most recent years labelled e.g. \"2025 (provisional)\". Its latest year is partial — deaths only through the data-through date the response names, against a full-year population — so its counts and rates read low next to a finished year, and a notice says so whenever the years queried include it. \"underlying_2018_2024\" (D158) is settled — not provisional — data for 2018–2024. \"multiple_1999_2020\" (D77) and \"multiple_2018_2024\" (D157) record every cause listed on the death certificate; without an mcd_icd10 filter they return the same figures as the underlying-cause database for the same era, so pick one only to use that filter. The two 1999–2020 databases report race in CDC's four bridged groups; the other three use the six single-race groups — figures broken out by race are not comparable between the two families.",
"enum": [
"underlying_1999_2020",
"provisional",
"underlying_2018_2024",
"multiple_1999_2020",
"multiple_2018_2024"
],
"type": "string"
},
"group_by": {
"default": [
"year"
],
"description": "Dimensions to break results out by (1–4, each at most once), in output-column order — e.g. [\"year\"], [\"year\",\"sex\"], [\"icd_chapter\",\"year\"]. Results are always national. \"race\" resolves to whichever race vocabulary the selected database uses — four bridged groups (Asian and Pacific Islander combined) on the 1999–2020 databases, six single-race categories on the others, one of them \"More than one race\" — so a race series from one family cannot be spliced onto one from the other. \"hispanic_origin\" splits Hispanic or Latino, Not Hispanic or Latino, and Not Stated. \"month\" groups by calendar month (labels such as \"Jan., 2019\") and returns deaths only: population and both rates are \"Not Applicable\". The rest group by underlying cause: \"icd_chapter\" and \"icd_subchapter\" by node of CDC's ICD-10 tree, each row carrying the node's code range as cause_code (e.g. \"C00-D48\"), which cause_icd10 takes as it stands; \"cause_113\" by CDC's 113-cause list, each row carrying cause_level, its depth in that nested list (1 for a top-level cause) — a deeper cause is already counted in the one containing it; \"leading_causes\" by the 15 leading causes, ranked by deaths, and only on its own — CDC refuses it beside any other dimension, though the filters still apply; \"injury_intent\" by intent (unintentional, suicide, homicide, undetermined, legal intervention, or no injury). The most values the listed dimensions can take, multiplied, must be 10,000 or fewer — e.g. icd_subchapter (177) × year (22 on the 1999–2020 databases) × sex (2) fits, and adding age_group (12) does not — or the call is refused before any request. year beside month, and icd_chapter beside icd_subchapter, add nothing to the product, since each month names its year and each sub-chapter sits inside one chapter.",
"items": {
"enum": [
"year",
"age_group",
"sex",
"race",
"icd_chapter",
"icd_subchapter",
"cause_113",
"leading_causes",
"injury_intent",
"hispanic_origin",
"month"
],
"type": "string"
},
"maxItems": 4,
"minItems": 1,
"type": "array"
},
"limit": {
"description": "Rows to return from the table CDC sent — any positive integer. Omit to take the rest of the table from offset, up to 10,000 rows. One call returns at most 10,000 rows: a larger limit is lowered to 10,000, and the response says so and gives a nextOffset when rows remain. WONDER's request carries no limit of its own, so this pages a table already fetched in full rather than narrowing the query: the deaths, rates, caveats and hidden-row notices are the same whichever page is read.",
"maximum": 9007199254740991,
"minimum": 1,
"type": "integer"
},
"mcd_icd10": {
"anyOf": [
{
"const": "",
"type": "string"
},
{
"enum": [
"999--999",
"999-999"
],
"type": "string"
},
{
"description": "ICD-10 code or range, same form as cause_icd10 — a chapter such as \"S00-T98\" (injury and poisoning, a chapter the underlying-cause finder does not list), a block such as \"J09-J18\" (influenza and pneumonia), or a single code such as \"T40.1\" (heroin).",
"pattern": "^[A-Z][0-9]{2}(\\.[0-9]+)?(-[A-Z][0-9]{2}(\\.[0-9]+)?)?$",
"type": "string"
},
{
"description": "A list of up to 50 entries, each in the single-value form, matched as a union: a death counts once when it matches any of them, so a code set such as X40–X44 plus X60–X64 is one series with one set of rates. Repeated entries are ignored. An empty list reads as omitted.",
"items": {
"anyOf": [
{
"enum": [
"999--999",
"999-999"
],
"type": "string"
},
{
"description": "ICD-10 code or range, same form as cause_icd10 — a chapter such as \"S00-T98\" (injury and poisoning, a chapter the underlying-cause finder does not list), a block such as \"J09-J18\" (influenza and pneumonia), or a single code such as \"T40.1\" (heroin).",
"pattern": "^[A-Z][0-9]{2}(\\.[0-9]+)?(-[A-Z][0-9]{2}(\\.[0-9]+)?)?$",
"type": "string"
}
],
"description": "One list entry: an ICD-10 code or range, or the withheld-cause marker."
},
"maxItems": 50,
"type": "array"
}
],
"description": "Filter to deaths with any of these ICD-10 codes recorded anywhere on the death certificate, whether or not it was the underlying cause — e.g. \"died with a respiratory condition listed\", a population no underlying-cause query can produce. Takes one code or range, or a list of them, e.g. opioid involvement as [\"T40.0\",\"T40.1\",\"T40.2\",\"T40.3\",\"T40.4\",\"T40.6\"]. Valid only when database is \"multiple_1999_2020\", \"multiple_2018_2024\", or \"provisional\"; the other databases record only the underlying cause and reject it. \"999--999\", the withheld-cause marker described under cause_icd10, is offered here too but only by \"provisional\", where the 24-week withholding also covers drug poisoning (T36-T50) as a listed cause. Combines with cause_icd10, which keeps meaning the underlying cause: a death must match both filters. Omit for all causes."
},
"offset": {
"default": 0,
"description": "Index of the first row to return, for continuing past a previous call (default 0, max 10,000). Rows keep the order CDC returned them in, which is stable for a given query, so offset plus limit walks the table without gaps or repeats. An offset at or past the row total returns an empty page rather than an error.",
"maximum": 10000,
"minimum": 0,
"type": "integer"
},
"sex": {
"default": "all",
"description": "Filter by sex.",
"enum": [
"all",
"male",
"female"
],
"type": "string"
},
"year_range": {
"description": "Inclusive year range; from must not be later than to. These bounds span every database (1999–2026); the years the selected one actually holds are narrower, and a range outside them is rejected with that database's span named. Omit for all years the database holds.",
"properties": {
"from": {
"description": "First year (1999–2026 across all databases; the selected one holds a narrower span).",
"maximum": 2026,
"minimum": 1999,
"type": "integer"
},
"to": {
"description": "Last year (1999–2026 across all databases; the selected one holds a narrower span).",
"maximum": 2026,
"minimum": 1999,
"type": "integer"
}
},
"required": [
"from",
"to"
],
"type": "object"
}
},
"type": "object"
},
"name": "cdc_query_wonder"
}
]
}What the leaf hashes
{"body":"50a5a5b67930efd539b11c073fb5c4ada93d21edcebeb8fd659b898358888898","id":1771344,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793547276459507,"prev":579719,"subject":"4c1c4905-c410-4c33-a30e-375bbbf46947","subject_kind":"endpoint"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (302406 rows).
- 0xc1288c1a57d4f78bbaabc5904566ac75ea76fca55a2546576cdb39e601569146
- 0xb73d4576408875a7d85f6983a4aeabd45093f3e42db936e9a97f4df890dd16b5
- 0xda7141499628b47cfffa189804cc1d48beee75e472a4c0e31e2ef492daf1c050
- 0x7a9b7c09a6ff477b7dd1adbf17beec7e437c2fecb12640d9f53f8d1fcce3efe6
- 0xf5eafa1a2d4904774f1aeaf57902bda3ae59b17521017336d1e67f93bcb686e7
- 0x4cea71d6000df2cf4446bb6ee030f74b8f5114744b92efd4709cb9c8b6d56d74
- 0x86638e80f16e337366781d63ba27898bb8bc83d07afd37113478f423d43a4264
- 0x460bad67052ca7a6ed31422ddf0a320626af8cf2d1f2a3068c6276632397a07b
- 0xec88469bd94d49ccd69654e65e502e0037ef6ab816cc854c9e1cb2b55fccfc4c
- 0x504f10eb2aafe366c56f20936db82f3b777b08a3bafe54408b3900e1f1824d57
- 0x4d554cd853064528124ab16e7eac98ec04648302411f01ad6a620dda758b0c28
- 0xbaf7d185d31e2c3874eff43313a49057924c943d0fe716b9713f2d944bdd851c
- 0xefe564ec44d50e51cc27963590ca317b9c3510aaf30351f2e937c01c07c486de
- 0x0c6f1e059ed2de7638825ab03396dd843c97d2de1abde6928871cfc5ef085a33
- 0xf6217f3e2344dd9bf8c6e296c4729fbf7611d258b93c45e1bbe5f62e65e8e714
- 0x8339aa87501c4d4f8b38a13e480a7c563957e09fb5711bed7cf189d6787f960d
- 0xb5916fb7a3e87dc0702e46eeadcd22652e2e1e755f8d429cc7a14a67a350b51b
- 0x6142ac48fda269c17791c79da99c2456ac6acfe98268f4d168a404fd6040c703
- 0x3315fd2757fdd435852cc277377234a3f3909a6d2a089d0e36f6d59aacfda910
- Day root
- 0x7fa2cba1cf3d6b35630896f5fe1a650adb307ea2c376e80a5f2d9276b7cb5ab3
- Chained
- 0x577ff89ba012beeff3197bcff7fa86752074bdf54205a24359cc437be2a952a4
- Published
- On Arc Testnet, block 70262758: 0x435bc1b9331471d72e1998f2e420983b5189d4da65ffbd6f27ef40daf5e1ea90