Dataset Cleaner & Exporter MCP server

Dataset Cleaner & Exporter (Remote MCP Server)

Deduplicate, flatten and clean messy JSON rows in a single tool call. Hand it a list of rows from a scraper, a CRM export or an API, and it hands back clean, spreadsheet-ready rows (or CSV text) plus an exact account of what was merged and why.

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

https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp

Free to use while in early access.

What it does

One call runs a fixed pipeline, in this order:

1. Expand (optional) one array field, such as offers or variants, into one row per entry, repeating the other fields.
2. Flatten nested objects into columns: address.city becomes address_city. Arrays stay as one JSON-text cell.
3. Clean every value: trim text, lowercase valid emails, reduce phone numbers to digits (keeping a leading +), lowercase URL hosts and drop the trailing slash, and optionally strip HTML and turn "42" and "true" into real numbers and booleans. Blank text becomes null.
4. Keep, remove or rename columns.
5. Deduplicate on the fields you name, or the whole row: exact, normalized (ignores case and whitespace, the default) or fuzzy (near-duplicates). The most complete row survives.

Deterministic, no AI in the loop, nothing guessed. A value it cannot confidently read, such as "not-an-email" in an email column, is left exactly as it was. The summary tells you how many rows came in, how many duplicates were removed, how many rows went out, how full every column is, and warns you when something needs a look, for example rows with an empty dedup key, which are kept as they are rather than merged with each other.

Tools

Connect

Claude Code

claude mcp add --transport http dataset-cleaner-exporter https://dataset-cleaner-exporter.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-cleaner-exporter": {
      "url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
    }
  }
}

Example

Five messy lead rows go in, two of them duplicates with different casing and whitespace:

{
  "rows": [
    {"company": "  Acme Corp  ", "email": "SALES@ACME.COM", "phone": "+1 (555) 123-4567", "website": "HTTPS://Acme.com/", "address": {"city": "Austin", "state": "TX"}},
    {"company": "Acme Corp", "email": "sales@acme.com ", "phone": "555.123.4567", "website": "https://acme.com", "address": {"city": "Austin", "state": ""}},
    {"company": "Globex Inc", "email": " Info@Globex.io", "phone": "+1 555 987 6543", "website": "https://globex.io/", "address": {"city": "Denver", "state": "CO"}, "notes": "<b>Hot</b> lead &amp; ready"},
    {"company": "globex inc", "email": "info@globex.io", "phone": "", "website": "", "address": {"city": "Denver", "state": "CO"}},
    {"company": "Initech", "email": "hello@initech.com", "phone": "(555) 010-0199", "website": "http://www.INITECH.com/about/", "address": {"city": "Dallas", "state": "TX"}}
  ],
  "dedupKeys": ["email"],
  "stripHtml": true
}

Three clean rows come out. Each duplicate pair kept its more complete row:

Shortened. The full README is on GitHub.