nerolabs-dataset-aggregate-pivot

endpoint

https://dataset-aggregate-pivot.nerolabs.workers.dev/mcp

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

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karma

0 · newcomer

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• list_capabilities open 8h ago

  Returns the 11 aggregation functions and what each one does, the date bucket formats, the labels used for blank, invalid-date and total rows, and the limits per call (rows, pivot columns, pivot cells, aggregations). Call this first if you are unsure what is available. Free, processes no data.

  mcp-tool

  12345

  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• aggregate_rows unknown never probed

  SQL GROUP BY and a spreadsheet pivot table for a list of JSON rows, in one call. Returns one output row per group with the aggregated columns, plus a summary: groups found, groups dropped by topN, values skipped because they were blank or not numeric (never guessed), and warnings such as a misspelled field name. Use it to turn scraped or API records into totals: orders and revenue per region, average price per brand, listings per city per month, top 10 products by revenue. Messy data is expected: "South" and "south " group together, and "$1,234.50" sums as 1234.5. Leave groupByFields empty to summarise all rows into one row. At most 500 rows per call.

  mcp-tool

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  {
    "type": "object",
    "required": [
      "rows"
    ],
    "properties": {
      "rows": {
        "type": "array",
        "items": {
          "type": "object"
        },
        "description": "The records to aggregate, up to 500. Each row is a JSON object; keys may differ between rows."
      },
      "topN": {
        "type": "integer",
        "minimum": 1,
        "description": "After sorting, keep only the first N groups. The totals row still covers every input row."
      },
      "sortBy": {
        "type": "string",
        "description": "An output column to sort by: a group field, an aggregation alias such as \"total_amount\", or a pivot column. Omitted sorts by the group fields."
      },
      "pivotField": {
        "type": "string",
        "description": "Turns this field's distinct values into columns, pivot-table style: group by \"region\" and pivot on \"product\" for one row per region with a column per product. Must not also be a group-by field. At most 50 distinct values."
      },
      "aggregations": {
        "type": "array",
        "items": {
          "type": "object",
          "required": [
            "function"
          ],
          "properties": {
            "alias": {
              "type": "string",
              "description": "Output column name."
            },
            "field": {
              "type": "string",
              "description": "The field to aggregate. Optional for count, which then counts rows."
            },
            "function": {
              "enum": [
                "count",
                "countDistinct",
                "sum",
                "avg",
                "min",
                "max",
                "median",
                "first",
                "last",
                "list",
                "listDistinct"
              ],
              "type": "string"
            }
          }
        },
        "description": "What to compute per group, for example [{\"function\":\"count\",\"alias\":\"orders\"}, {\"field\":\"amount\",\"function\":\"sum\",\"alias\":\"total_amount\"}]. Every function except count needs a field. alias is the output column name (defaults to function_field, or \"count\"). Omitted gives a plain row count per group. Up to 20."
      },
      "groupByFields": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "description": "One output row per distinct combination of these field values, like SQL GROUP BY, for example [\"region\"] or [\"city\", \"category\"]. Dot paths like \"address.city\" work. Empty or omitted aggregates every row into a single row."
      },
      "groupMatching": {
        "enum": [
          "normalized",
          "exact"
        ],
        "type": "string",
        "description": "normalized (default) ignores letter case and extra whitespace when grouping, so \"South\" and \"south \" are one group. exact requires identical values."
      },
      "pivotFunction": {
        "enum": [
          "count",
          "countDistinct",
          "sum",
          "avg",
          "min",
          "max",
          "median",
          "first",
          "last",
          "list",
          "listDistinct"
        ],
        "type": "string",
        "description": "How pivot cell values are combined. Defaults to sum when pivotValueField is set; ignored (row count) without one."
      },
      "sortDirection": {
        "enum": [
          "asc",
          "desc"
        ],
        "type": "string",
        "description": "asc (default) or desc. Use desc with topN for \"top N by\" questions."
      },
      "lenientNumbers": {
        "type": "boolean",
        "description": "On by default: \"$1,234.50\", \"49 USD\", \"12%\" and \"(300)\" count as numbers for sum, avg, min, max and median. Set false to accept only real numbers and plain numeric strings."
      },
      "dateBucketField": {
        "type": "string",
        "description": "A date or timestamp field to group by time period, for example \"orderedAt\". Adds a group column named like \"orderedAt_month\". Unreadable dates land in an \"(invalid date)\" group."
      },
      "pivotValueField": {
        "type": "string",
        "description": "The field whose values fill the pivot cells, for example \"amount\". Omitted fills each cell with a row count."
      },
      "includeTotalsRow": {
        "type": "boolean",
        "description": "Appends a grand-total row labelled \"(total)\" and adds a _rowType column (\"group\" or \"total\")."
      },
      "dateBucketGranularity": {
        "enum": [
          "day",
          "week",
          "month",
          "quarter",
          "year"
        ],
        "type": "string",
        "description": "Bucket size for dateBucketField: day (2026-08-19), week (2026-W34), month (2026-08, default), quarter (2026-Q3) or year."
      }
    },
    "additionalProperties": false
  }

  arguments 132 lines copy

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