Dataset Aggregate & Pivot

io.github.Nero-EnginePublished by GitHub account Nero-Enginev0.1.0Updated Oct 24, 2026

GROUP BY and pivot tables for JSON rows: 11 functions, date buckets, top N, totals, messy numbers.

The publisher's own server: Aggregate

VerifiedStreamable HTTPWeb executableDatabasesData & Analytics

Overview

AI-generated overview

A remote MCP server that groups, aggregates and pivots JSON rows like SQL GROUP BY or a spreadsheet pivot table, returning one summary row per group.

What you can do
Group, aggregate, pivot, sort and total JSON rows in one call, with date buckets by day, week, month, quarter or year and top N plus grand totals. List the 11 aggregation functions, date bucket formats, blank and invalid-date labels, and per-call limits. Read messy values such as currency strings and inconsistent casing, and report skipped or non-numeric values and misspelled fields instead of guessing.
When to use it
Useful when an assistant has a list of rows from a scraper, API or spreadsheet and needs a quick grouped summary, pivot or top-N table without writing code or loading a database.
Requirements
A remote streamable HTTP endpoint; no install, API key or signup. Rows are passed inline as JSON, with limits of 500 rows, 50 pivot columns, 5,000 pivot cells and 20 aggregations per call.
Before you install
Rows are sent to a third-party hosted service. The README says data is processed in memory and not stored, while each call logs the tool name, row counts, success, client name, country and a hashed caller ID. Avoid sending sensitive rows, and note that median and distinct counts cannot be combined across batches.

Installation

In SourceWeft

  1. Open Dataset Aggregate & Pivot in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.Nero-Engine%2Fdataset-aggregate-pivot/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "dataset-aggregate-pivot": {
      "type": "http",
      "url": "https://dataset-aggregate-pivot.nerolabs.workers.dev/mcp"
    }
  }
}

README

Dataset Aggregate & Pivot (Remote MCP Server)

SQL GROUP BY and spreadsheet pivot tables for messy JSON rows, in a single tool call. Hand it a list of rows from a scraper, an API or a spreadsheet, say what to group by and what to compute, and it hands back one clean summary row per group plus an exact account of anything it skipped.

Built for AI agents. No install, no API key, no signup. Connect by URL and call it.

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

Free to use while in early access.

What it does

One call runs the whole summary, in this order:

  1. Group the rows by one or several fields (dot paths like address.city work), or leave the group fields empty to summarise every row into one. Add a date bucket to group a date or timestamp by day, ISO week, month, quarter or year (orderedAt becomes orderedAt_month = 2026-08).
  2. Aggregate each group with any of 11 functions: count, countDistinct, sum, avg, min, max, median, first, last, list and listDistinct, each with its own output column name.
  3. Pivot one field's distinct values into columns: group by region, pivot on product, fill the cells with the sum of amount, and get one row per region with a column per product, zero-filled where a combination has no rows.
  4. Sort by any output column, keep the top N groups, and add a grand-total row that still covers every input row.

Messy data is the normal case. South, south and SOUTH land in one group with one label. "$1,234.50", "49 USD", "1.234,50" and "(300)" are read as numbers. Values that genuinely are not numbers, like "n/a", are never guessed at: they are left out and counted in the summary, and a misspelled field name comes back as a warning instead of a silently empty result.

Tools

ToolWhat it does
list_capabilitiesLists the 11 aggregation functions, the date bucket formats, the labels used for blank, invalid-date and total rows, and the limits per call. Processes no data.
aggregate_rowsGroups, aggregates, pivots, sorts and totals the rows you pass, and returns the summary rows plus a report of groups found, groups dropped by top N, skipped values and warnings.

Connect

Claude Code

bash
claude mcp add --transport http dataset-aggregate-pivot https://dataset-aggregate-pivot.nerolabs.workers.dev/mcp

Claude Desktop / claude.ai: Settings, Connectors, Add custom connector, paste the URL above.

Cursor, Windsurf, VS Code and other MCP clients

json
{  "mcpServers": {    "dataset-aggregate-pivot": {      "url": "https://dataset-aggregate-pivot.nerolabs.workers.dev/mcp"    }  }}

Example

Eight messy order rows go in, with orders per region and each product's revenue pivoted into its own column:

json
{  "rows": [    {"orderId": 1001, "region": "North", "product": "Widget", "amount": "$1,200.00", "orderedAt": "2026-07-03"},    {"orderId": 1002, "region": "North", "product": "Gadget", "amount": 350, "orderedAt": "2026-07-18"},    {"orderId": 1003, "region": "South", "product": "Widget", "amount": "890.50", "orderedAt": "2026-07-22"},    {"orderId": 1004, "region": "south", "product": "Gizmo", "amount": 120, "orderedAt": "2026-08-02"},    {"orderId": 1005, "region": "East", "product": "Widget", "amount": 2400, "orderedAt": "2026-08-05"},    {"orderId": 1006, "region": "East", "product": "Gadget", "amount": "n/a", "orderedAt": "2026-08-09"},    {"orderId": 1007, "region": "North", "product": "Gizmo", "amount": 75, "orderedAt": "2026-08-11"},    {"orderId": 1008, "region": "", "product": "Widget", "amount": 410, "orderedAt": "2026-08-14"}  ],  "groupByFields": ["region"],  "aggregations": [{"function": "count", "alias": "orders"}],  "pivotField": "product",  "pivotValueField": "amount",  "pivotFunction": "sum"}

Four summary rows come out. South and south became one group, "$1,200.00" summed as 1200, the row with no region is kept visibly as (blank), and the "n/a" amount was skipped and reported rather than treated as a number:

json
{  "rows": [    {"region": "(blank)", "orders": 1, "Gadget": 0, "Gizmo": 0, "Widget": 410},    {"region": "East", "orders": 2, "Gadget": 0, "Gizmo": 0, "Widget": 2400},    {"region": "North", "orders": 3, "Gadget": 350, "Gizmo": 75, "Widget": 1200},    {"region": "South", "orders": 2, "Gadget": 0, "Gizmo": 120, "Widget": 890.5}  ],  "summary": {    "inputRowCount": 8,    "groupCount": 4,    "outputRowCount": 4,    "pivot": {"field": "product", "valueField": "amount", "function": "sum", "distinctValues": 3},    "columns": ["region", "orders", "Gadget", "Gizmo", "Widget"],    "skippedValues": {"pivot:Gadget": 1}  }}

Add "sortBy": "orders", "sortDirection": "desc", "topN": 10, "includeTotalsRow": true to the same call for a top 10 with a grand total, or "dateBucketField": "orderedAt" for one row per region per month.

Limits

  • Up to 500 rows per call. Anything larger returns a clear message rather than failing silently. Batches can be summarised separately for sum, count, min and max, and an average rebuilt as total sum divided by total count, but a median or a distinct count cannot be combined across batches.
  • Up to 50 pivot columns and 5,000 pivot cells (groups multiplied by pivot columns) per call, so a pivot on a near-unique field such as an ID is refused with advice instead of returning hundreds of columns.
  • Up to 20 aggregations per call.
  • Rows are passed inline as JSON.

Privacy

Your rows are processed in memory and never stored. To see which tools get used, each call records the tool name, row counts, whether it succeeded, the client name your app reports, the country and a one-way hashed caller ID. Your data, your arguments and your IP address are never kept in that log.

Also available

The same engine runs on the Apify Store as Dataset Aggregate, Group By & Pivot, which also reads Apify datasets, CSV, TSV, Excel, JSON and JSON Lines files and Google Sheets by URL, handles up to 200,000 rows per run, exports the summary as a CSV or Excel file, appends it to a named dataset that accumulates across scheduled runs, and posts it to a webhook.

Built by Nero Labs.

Source: README.md at commit 3b22ee2

Tools

2

list_capabilities

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.

Takes no parameters.

aggregate_rows

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.

ParametersrowsrequiredtopNsortBypivotFieldaggregationsgroupByFieldsgroupMatchingpivotFunctionsortDirectionlenientNumbersdateBucketFieldpivotValueField+2 more

Version history

1
  1. v0.1.0LatestSep 16, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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