StatsMapped Public Data

Public statistics for Ireland and the UK: housing, crime, health, economy, welfare, with caveats.

使うべきか

品質と安全性

A
説明の品質
100%
スキーマの完全性
66%
命名の品質
90%
ポイズニングのリスク
100%
権限の一致
100%
プロトコルへの準拠
100%

ツール定義とプロトコルへの準拠に関する自動分析に基づいています。

コンテキストコスト

~2,446トークン数(ツール定義)
~1.5 KB一般的なレスポンスサイズ
注意への影響は中程度(128k コンテキストの 1.91%)

これは、サーバーのツールがモデルのコンテキストに読み込まれるたびに消費されるおおよそのトークン数です。数が多いほど、ほかのタスクに使える注意が減ります。

インストール

ワンクリックインストール

これを `claude_desktop_config.json` ファイルに追加してください:

{
  "mcpServers": {
    "public-data": {
      "command": "uvx",
      "args": [
        "statsmapped-mcp"
      ]
    }
  }
}

実行可能なパッケージ

pypistatsmapped-mcp0.3.2stdio

リモートエンドポイント

https://mcp.statsmapped.com/mcpstreamable-http

できること

ツール一覧

ツール(4)

🟢 読み取り専用🟡 書き込み🔴 削除⚪ 不明
🟢query_data(area_id, dataset, history_months, country)

Three modes, depending on which of `area_id`/`dataset` are given -- consolidates what were three separate tools (list_datasets, list_area_datasets, get_dataset_for_area) behind one, since they are all really "how do I get data" at different levels of specificity: 1. Neither `area_id` nor `dataset`: lists every dataset (stat) StatsMapped tracks for one country ('ireland' or 'united-kingdom'), with its key, human label, and which geography levels it can be shown at. Ireland and the UK track genuinely different datasets -- call this first for the right country before assuming a stat_key exists there, to find the right `stat_key` for `compare`'s ranking mode. 2. `area_id` given, `dataset` omitted: lists every dataset available for that one area (e.g. "county:kerry" for Ireland, "uk:lad:e09000033" for the UK), with its latest figure, year-on-year change, and caveat labels only (not full caveat text -- use mode 3 for the full detail on any one dataset that matters). `area_id` comes from `list_areas`; `country` must match whichever country that call used, or this simply 404s ("unknown geography"). 3. Both `area_id` and `dataset` given: full detail for one dataset in one area -- the latest figure, a written summary, full caveat text, and (if `history_months` is set) recent history. `dataset` is a `series_key` from mode 2's own response. `history_months` means actual months of history (0 = everything) -- e.g. 24 returns 2 years of an annual series, not 24 years. `country` must match `area_id`'s own country. `dataset` and `history_months` are only meaningful together with `area_id` (and, for `history_months`, `dataset` too, since it only applies to mode 3); giving either without its real precondition raises rather than silently dropping the argument and dispatching to the wrong mode.

入力スキーマ

{
  "type": "object",
  "properties": {
    "area_id": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Area Id"
    },
    "dataset": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Dataset"
    },
    "history_months": {
      "default": 0,
      "title": "History Months",
      "type": "integer"
    },
    "country": {
      "default": "ireland",
      "title": "Country",
      "type": "string"
    }
  },
  "title": "query_dataArguments"
}

出力スキーマ

{
  "type": "object",
  "properties": {
    "result": {
      "anyOf": [
        {
          "items": {
            "additionalProperties": true,
            "type": "object"
          },
          "type": "array"
        },
        {
          "additionalProperties": true,
          "type": "object"
        }
      ],
      "title": "Result"
    }
  },
  "required": [
    "result"
  ],
  "title": "query_dataOutput"
}
🟢list_areas(level, country)

List every geography at one boundary level, for one country ('ireland' or 'united-kingdom'). `level` defaults to "county" (Ireland's 26 counties); the UK's own primary level is "lad" (local authority districts), not "county". Other levels exist per country (e.g. Ireland's "local_authority", "garda_division") -- see a dataset's own `compatible_levels` from `query_data` for which levels a given stat is actually published at. Returns each area's `id` (used by `query_data`'s area-scoped modes, always paired with the SAME `country`) and `name`.

入力スキーマ

{
  "type": "object",
  "properties": {
    "level": {
      "default": "county",
      "title": "Level",
      "type": "string"
    },
    "country": {
      "default": "ireland",
      "title": "Country",
      "type": "string"
    }
  },
  "title": "list_areasArguments"
}

出力スキーマ

{
  "type": "object",
  "properties": {
    "result": {
      "items": {
        "additionalProperties": true,
        "type": "object"
      },
      "title": "Result",
      "type": "array"
    }
  },
  "required": [
    "result"
  ],
  "title": "list_areasOutput"
}
🟢compare(stat_key, level, pair_key, stat_key_a, stat_key_b, ...)

Four modes, depending on which arguments are given -- consolidates what were four separate tools (rank_areas, list_comparisons, get_comparison, check_comparability) behind one, since they are all really "how does this stat compare" at different scopes. Exactly one mode's arguments should be given; mixing arguments from different modes (e.g. both `stat_key` and `pair_key`, or only one of `stat_key_a`/`stat_key_b`) raises an error rather than silently guessing which mode was meant. 1. `stat_key` alone (no `pair_key`, no `stat_key_a`/`stat_key_b`): ranks every area at one geography level by its latest figure for that stat, for one country -- e.g. "which counties have the highest median sale price" (country="ireland"). `stat_key` comes from `query_data`'s dataset-listing mode, for the SAME country. `level` omitted uses this ranking's own default level; pass one of that dataset's own `compatible_levels` for a different one -- a level this ranking doesn't have registered returns an empty list rather than an error. Where the underlying stat has no honest per-area denominator (crime, homelessness, live_register and similar -- StatsMapped's own RANKING_NO_DENOMINATOR_STATS), each row's `rate_per_1000` is the real figure to rank/compare by, not `latest_value`, which is a raw count dominated by area population size. Always carry forward every entry in `caveats` when using a row in an answer. 2. `pair_key` alone: full detail for one registered comparison pair -- each axis's label, unit and publisher, the correlation stats (r, rho, and a leave-one-out sensitivity range naming the single most influential area), and caveats. `pair_key` comes from mode 4's own response, for the SAME country. 3. Both `stat_key_a` and `stat_key_b` given: does StatsMapped have a registered, hand-vetted comparison between these two stats? Registry- backed only -- never computes a fresh correlation for an arbitrary pair. Both stat_keys come from `query_data`'s dataset-listing mode, for the SAME country. `verdict` is one of `"SUPPORT"` (a real, hand-vetted registered pair with no open caveats -- may be treated as a confirmed relationship), `"QUALIFY"` (hand-vetted, but the evidence carries real caveats -- e.g. no robustness check for outliers, or an unverified geography-level join; read `uncertainty` and `reasons` before presenting it as confirmed), `"REJECT"` (a real structural impossibility or a human-vetted "no" -- the two stats share no geography level at all, or a reviewer rejected this exact pairing), or `"INSUFFICIENT"` (not registered, not ruled out either -- StatsMapped genuinely hasn't vetted this pair; never treat this as "probably comparable"). `uncertainty` names 4 separate dimensions (data_quality, comparability, statistical_strength, causal_strength) -- `causal_strength` is always `"not_established"`, since no comparison here implies causation regardless of verdict. `comparable` (DEPRECATED, kept only for callers that haven't migrated) collapses `verdict` to the old 3-way yes/no/unknown -- `"yes"` for both `SUPPORT` and `QUALIFY` (both mean "hand-vetted", the old `comparable` meaning this field has always carried; the caveats a `QUALIFY` pair carries live in `uncertainty`/`reasons`, not in demoting `comparable`), `"no"` for `REJECT`, `"unknown"` for `INSUFFICIENT`. Prefer `verdict` directly when you need to distinguish a fully-confirmed `SUPPORT` from a caveated `QUALIFY`. Read `reasons` before presenting any answer other than `"SUPPORT"` as unqualified. 4. None of the above given: lists every registered cross-dataset comparison pair for one country -- e.g. "median sale price vs new dwelling completions per 1,000 residents". A small, hand-curated set, not an arbitrary-pair engine: pass one of the returned `pair_key` values to mode 2 for the real correlation and axis detail. `level` is only meaningful together with `stat_key` (mode 1); giving it without `stat_key` raises rather than silently dropping it and falling through to mode 4's unrelated pair listing.

入力スキーマ

{
  "type": "object",
  "properties": {
    "stat_key": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Stat Key"
    },
    "level": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Level"
    },
    "pair_key": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Pair Key"
    },
    "stat_key_a": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Stat Key A"
    },
    "stat_key_b": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Stat Key B"
    },
    "country": {
      "default": "ireland",
      "title": "Country",
      "type": "string"
    }
  },
  "title": "compareArguments"
}

出力スキーマ

{
  "type": "object",
  "properties": {
    "result": {
      "anyOf": [
        {
          "items": {
            "additionalProperties": true,
            "type": "object"
          },
          "type": "array"
        },
        {
          "additionalProperties": true,
          "type": "object"
        }
      ],
      "title": "Result"
    }
  },
  "required": [
    "result"
  ],
  "title": "compareOutput"
}
🟢explain_metric(stat_key, country)

Definition, methodology and standing caveats for ONE stat ('ireland' or 'united-kingdom') -- never a current figure. Call this when the question is about what a metric MEANS or how it's measured ("how is the claimant count defined", "is this a mean or a median"), not about a specific area's value -- `query_data`/`compare` already answer that. `stat_key` comes from `query_data(country=...)` for the SAME country.

入力スキーマ

{
  "type": "object",
  "properties": {
    "stat_key": {
      "title": "Stat Key",
      "type": "string"
    },
    "country": {
      "default": "ireland",
      "title": "Country",
      "type": "string"
    }
  },
  "required": [
    "stat_key"
  ],
  "title": "explain_metricArguments"
}

出力スキーマ

{
  "type": "object",
  "additionalProperties": true,
  "title": "explain_metricDictOutput"
}

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