Dataset Filter & Transform

io.github.Nero-Enginev0.1.0更新于 Sep 29, 2026

Clean, filter and reshape JSON rows in one call: 26 transforms, 25 filters, sort, dedupe, limit.

已验证Streamable HTTP可网页运行Other

安装

在 SourceWeft 中

  1. 打开 控制台中的 Dataset Filter & Transform，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

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

README

Dataset Filter & Transform (Remote MCP Server)

Clean, filter and reshape messy JSON rows in a single tool call. Hand it a list of rows from a scraper, an API or a spreadsheet, tell it how to reshape them and which rows to keep, and it hands back clean rows plus an exact account of what was removed and why.

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

https://dataset-filter-transform.nerolabs.workers.dev/mcp

Free to use while in early access.

What it does

One call runs a full pipeline, in this order:

  1. Transform every row: rename, drop or keep fields, trim, change case, cast strings to numbers, compute new fields with arithmetic, extract with regex, split, replace, format dates, measure date gaps, pull the domain from an email or URL, hash, map values, parse JSON, and more (26 operations).
  2. Filter out the rows you do not want: equals, contains, starts with, greater than, between, is empty, matches regex, in a list, array contains, date before or after, within the last N days, and more (25 operators), combined with AND or OR.
  3. Sort, de-duplicate on any fields, and offset / limit.

Transforms run before filters, so you can create a field and filter on it in the same call.

It is honest about what it could not do. If a price like "not a price" cannot become a number, the row is not silently guessed at: the summary reports cast:price: 1.

Tools

ToolWhat it does
list_capabilitiesLists every transform operation and filter operator, the pipeline order and the row limit. Processes no data.
process_rowsRuns the pipeline on the rows you pass and returns the kept rows plus a summary.

Connect

Claude Code

bash
claude mcp add --transport http dataset-filter-transform https://dataset-filter-transform.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-filter-transform": {      "url": "https://dataset-filter-transform.nerolabs.workers.dev/mcp"    }  }}

Example

Five messy lead rows go in:

json
{  "rows": [    {"company": "  Acme Ltd  ", "e_mail": "[email protected]", "price": "$1,234.50", "qty": "3", "country": "uk"},    {"company": "Beta Systems", "e_mail": "[email protected]", "price": "49 USD", "qty": "1", "country": "UK"},    {"company": "Gamma GmbH", "e_mail": "[email protected]", "price": "€900", "qty": "2", "country": "DE"},    {"company": "Acme Ltd", "e_mail": "[email protected]", "price": "$1,234.50", "qty": "3", "country": "UK"},    {"company": "Delta Co", "e_mail": "", "price": "not a price", "qty": "5", "country": "UK"}  ],  "transforms": [    {"op": "trim", "field": "company"},    {"op": "rename", "from": "e_mail", "to": "email"},    {"op": "lowercase", "field": "email"},    {"op": "cast", "field": "price", "to": "number"},    {"op": "cast", "field": "qty", "to": "number"},    {"op": "compute", "field": "orderValue", "expression": "price * qty", "round": 2},    {"op": "extractDomain", "field": "email", "into": "domain"}  ],  "filters": [    {"field": "country", "operator": "equals", "value": "UK"},    {"field": "orderValue", "operator": "greaterThan", "value": 100}  ],  "sortBy": [{"field": "orderValue", "direction": "desc"}],  "distinctBy": ["domain"]}

One clean row comes out, with a summary of exactly why the other four went:

json
{  "rows": [    {"company": "Acme Ltd", "price": 1234.5, "qty": 3, "country": "uk", "email": "[email protected]", "orderValue": 3703.5, "domain": "acme.co.uk"}  ],  "summary": {    "inputRowCount": 5,    "keptRowCount": 1,    "excludedByFilter": 3,    "duplicatesRemoved": 1,    "transformIssues": {"cast:price": 1, "compute:orderValue": 1, "extractDomain:email": 1}  }}

Text matching is case-insensitive by default, and values like "$1,234.50", "49 USD" and "12%" are read as numbers unless you turn that off.

Limits

Up to 500 rows per call. For bigger lists, split them across several calls. Anything larger returns a clear message rather than failing silently.

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 Filter & Transform, which also reads Apify datasets, CSV and Excel files and Google Sheets, and exports CSV or Excel.

Built by Nero Labs.

来源：README.md，提交 a730a61

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版本历史

1
  1. v0.1.0最新Sep 16, 2026