Skip to content
verify mcp Beta VerifyMCP is currently in beta. If you notice any issues, get in touch and we’ll put it right.

Dataset Cleaner & Exporter

REMOTE · DATASET-CLEANER-EXPORTER.NEROLABS.WORKERS.DEV · SCANNED SEP 21

Dedupe, flatten and clean messy JSON rows (emails, phones, URLs, HTML) in one call, as JSON or CSV.

+3 this week 60 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →

Endpoint Security46
Transport & Reachability100
Schema Quality & AI Usability65
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 904 tokens (~452/item across 2 items; 2 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 2 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities60
  • Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
Install

How do I install the Dataset Cleaner & Exporter MCP server?

Dataset Cleaner & Exporter is a hosted endpoint at https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

remote · dataset-cleaner-exporter.nerolabs.workers.dev

# add to Claude Code
claude mcp add --transport http nero-engine-dataset-cleaner-exporter 'https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp'
// .cursor/mcp.json
{
  "mcpServers": {
    "nero-engine-dataset-cleaner-exporter": {
      "url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "nero-engine-dataset-cleaner-exporter": {
      "type": "http",
      "url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
    }
  }
}
# ~/.codex/config.toml
[mcp_servers.nero-engine-dataset-cleaner-exporter]
url = "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "nero-engine-dataset-cleaner-exporter": {
      "type": "remote",
      "url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add nero-engine-dataset-cleaner-exporter --url 'https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp' --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  nero-engine-dataset-cleaner-exporter:
    url: "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "nero-engine-dataset-cleaner-exporter": {
      "Transport": "http",
      "Url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
    }
  }
}
# add to Vellum
assistant mcp add nero-engine-dataset-cleaner-exporter -t streamable-http -u 'https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp'
// mcp.json
{
  "mcpServers": {
    "nero-engine-dataset-cleaner-exporter": {
      "type": "http",
      "url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 20 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

  • 18 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

  • 16 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

  • 14 Sept 26 0
    • Stability: unverified → 0.03 functional
  • 13 Sept 26 57

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 21 Sept 2026 · Probed https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=nerolabs.workers.dev CN=YE2,O=Let's Encrypt,C=US 12 Sept 2026 11 Dec 2026 ECDSA 256 ECDSA-SHA384 6f7f02a43942bb2aca3c411aec703cf0dc1
SANs: *.nerolabs.workers.dev, nerolabs.workers.dev
CN=YE2,O=Let's Encrypt,C=US (CA) CN=Root YE,O=ISRG,C=US 3 Sept 2025 2 Sept 2028 ECDSA 384 ECDSA-SHA384 4df3b15dd6c0784c507cd37b58e6f115
CN=Root YE,O=ISRG,C=US (CA) CN=ISRG Root X2,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 ECDSA-SHA384 872165fc34b6e5fba8add5b3705fb53a
CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) CN=ISRG Root X1,O=Internet Security Research Group,C=US 13 May 2026 2 Sept 2032 ECDSA 384 SHA256-RSA 6c8f1dc727c7117f7baf853ac980f9cd

Background: What to check on a remote MCP endpoint →

DNSSEC insecure

Validation of dataset-cleaner-exporter.nerolabs.workers.dev. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
dev. present 60074 8 Verified
workers.dev. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200

Background: How OAuth 2.1 works in the 2026 MCP spec →

Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp Verified 200
http (plaintext) http://dataset-cleaner-exporter.nerolabs.workers.dev/mcp Inconclusive 405
MCP tools · 2 exposed · ~861 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
clean_rows ~792

Deduplicates, flattens and cleans a list of JSON rows in one call and returns spreadsheet-ready rows (or CSV text) plus a summary with exact counts: rows in, rows added by expansion, duplicates removed, rows dropped by maxItems, rows out, the final column list, per-column fill rates and warnings. Steps, in order: optionally explode one array field into one row per entry; flatten nested objects into columns (address.city becomes address_city); trim text; lowercase valid emails; reduce phone numbers to digits with any leading +; lowercase URL hosts and drop the trailing slash; optionally strip HTML and turn numeric or true/false text into numbers and booleans; blank text becomes null; keep, remove or rename columns; then remove duplicates (normalized by default, comparing the whole row unless dedupKeys is set) keeping the most complete row. Deterministic, no AI, nothing guessed. Use it on scraped leads, CRM exports or API results before loading them anywhere. There is a row limit per call (see list_capabilities); split bigger lists across several calls.

NameTypeReqDescription
cleanFieldsbooleanDefault true. Normalize emails, phone numbers and URLs, detected by field name or value shape.
coerceTypesbooleanDefault false. Turn "42" into 42 and "true" into true. Leading-zero values like "007" stay text.
columnRenameMapRename columns after keep/remove, as ["oldName:newName"] or {"oldName":"newName"}, for example {"Details_founded":"founded"}.
columnsToKeeparrayKeep only these columns (flattened names). Takes priority over columnsToRemove.
columnsToRemovearrayDrop these columns (flattened names). Ignored if columnsToKeep is set.
dedupKeysarrayFields that identify a duplicate, for example ["Email"]. Empty compares the whole row. Use the final column names: flattened (Details_founded) and renamed. Exact and case-sensitive. Rows where every…
dedupModestringHow duplicates are found. normalized (default) ignores case and whitespace; exact needs identical values; fuzzy also merges near-duplicates (up to 100 rows and 1000 characters of key text, so name a…
dropEmptyFieldsbooleanDefault false. Remove null and empty fields from each row.
emptyToNullbooleanDefault true. Blank text becomes null.
expandArrayFieldstringOptional. One top-level array field (for example "offers") to explode into one row per entry, repeating the other fields. Object entries become columns. The expanded total must stay within the row li…
flattenbooleanDefault true. Turn nested objects into flat columns. Arrays become one JSON-text cell.
flattenSeparatorstringJoins nested key paths when flattening. Default "_".
keepStrategystringWhich duplicate survives: most_complete (default, fewest empty fields), first or last.
maxItemsintegerOptional cap: read at most this many rows and return at most this many. 0 (default) means no cap.
outputFormatstringjson (default) returns rows; csv returns the same result as CSV text in "csv" instead.
rowsarrayyesThe rows to clean. Each row is a JSON object; keys may differ between rows and values may be nested.
similarityThresholdnumberFuzzy mode only. 0.5 to 0.99, default 0.9. Higher is stricter.
stripHtmlbooleanDefault false. Remove HTML tags and decode common entities in text.

No output schema declared.

No examples provided.

list_capabilities ~69

Returns the exact cleaning rules (how emails, phone numbers and URLs are detected and normalized), the dedup modes and keep strategies, the order the steps run in, and the maximum rows per call. Call this first if you are unsure how a field will be treated. Free, processes no data.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

Common questions

What is the Dataset Cleaner & Exporter MCP server?

Dataset Cleaner & Exporter is an MCP server listed in the public MCP registry as io.github.Nero-Engine/dataset-cleaner-exporter. Dedupe, flatten and clean messy JSON rows (emails, phones, URLs, HTML) in one call, as JSON or CSV. This page covers its hosted endpoint (https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp).

Is the Dataset Cleaner & Exporter MCP server safe to use?

Dataset Cleaner & Exporter scores 60 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the Dataset Cleaner & Exporter MCP server expose?

Dataset Cleaner & Exporter exposes 2 tools: list_capabilities, clean_rows. Their descriptions and schemas cost roughly 861 tokens of context every time the server is loaded.

Does the Dataset Cleaner & Exporter MCP server require authentication?

No. We connected to Dataset Cleaner & Exporter without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

Is the Dataset Cleaner & Exporter MCP server still maintained?

Dataset Cleaner & Exporter is still listed as active in the MCP registry. We last reached this channel on 21 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.