Dataset Filter & Transform MCP server

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

Connect

Claude Code

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

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

Example

Five messy lead rows go in:

{
  "rows": [
    {"company": "  Acme Ltd  ", "e_mail": "Sales@ACME.co.uk", "price": "$1,234.50", "qty": "3", "country": "uk"},
    {"company": "Beta Systems", "e_mail": "hi@beta.io", "price": "49 USD", "qty": "1", "country": "UK"},
    {"company": "Gamma GmbH", "e_mail": "info@gamma.de", "price": "€900", "qty": "2", "country": "DE"},
    {"company": "Acme Ltd", "e_mail": "sales@acme.co.uk", "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": ["domai

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

{
  "rows": [
    {"company": "Acme Ltd", "price": 1234.5, "qty": 3, "country": "uk", "email": "sales@acme.co.uk", "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}
  }
}

Shortened. The full README is on GitHub.