Dataset Cleaner & Exporter MCP
A remote MCP server that allows agents to deduplicate, flatten, and clean messy JSON rows containing emails, phones, URLs, and HTML. It supports exporting data as JSON or CSV with a maximum of 150 rows per call.
Endpoint and access
No sign-in to connect and list tools. Individual tools may still need a vendor account, credentials, or permissions; check the documented prerequisites.
https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpWhat its tools do
2 tools, grouped by the hints the server advertises. Hints are self-declared, not verified behavior.
Not annotated (2)
Checks and signals
Each line is separate evidence, not a trust score.
- Passed Endpoint answered the live check ·
- Availability 1 of 1 checks passed in 30 days
What you can do with it
- Deduplicate messy JSON rows
- Flatten nested JSON structures
- Clean emails, phones, and URLs
- Export cleaned data as JSON or CSV
Source and maintenance
- Maintenance checked
Protocol and capabilities
- Server
- nerolabs-dataset-cleaner-exporter 0.1.0
- MCP protocol negotiated in check
- 2025-06-18
- Tools
- 2 advertised
- Resources
- Not advertised
- Resource templates
- Not advertised
- Prompts
- Not advertised
{
"tools": {
"listChanged": false
}
}Server-provided instructions
Untrusted server output shown for inspection. It is not Koskamo guidance and is excluded from knowledge search.
Tools
2 advertised
list_capabilities
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.
{
"type": "object",
"properties": {},
"additionalProperties": false
}clean_rows
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.
{
"type": "object",
"required": [
"rows"
],
"properties": {
"rows": {
"type": "array",
"items": {
"type": "object"
},
"description": "The rows to clean. Each row is a JSON object; keys may differ between rows and values may be nested."
},
"flatten": {
"type": "boolean",
"description": "Default true. Turn nested objects into flat columns. Arrays become one JSON-text cell."
},
"maxItems": {
"type": "integer",
"minimum": 0,
"description": "Optional cap: read at most this many rows and return at most this many. 0 (default) means no cap."
},
"dedupKeys": {
"type": "array",
"items": {
"type": "string"
},
"description": "Fields 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 key is empty count as duplicates of each other."
},
"dedupMode": {
"enum": [
"none",
"exact",
"normalized",
"fuzzy"
],
"type": "string",
"description": "How 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 short field in dedupKeys); none keeps every row."
},
"stripHtml": {
"type": "boolean",
"description": "Default false. Remove HTML tags and decode common entities in text."
},
"cleanFields": {
"type": "boolean",
"description": "Default true. Normalize emails, phone numbers and URLs, detected by field name or value shape."
},
"coerceTypes": {
"type": "boolean",
"description": "Default false. Turn \"42\" into 42 and \"true\" into true. Leading-zero values like \"007\" stay text."
},
"emptyToNull": {
"type": "boolean",
"description": "Default true. Blank text becomes null."
},
"keepStrategy": {
"enum": [
"most_complete",
"first",
"last"
],
"type": "string",
"description": "Which duplicate survives: most_complete (default, fewest empty fields), first or last."
},
"outputFormat": {
"enum": [
"json",
"csv"
],
"type": "string",
"description": "json (default) returns rows; csv returns the same result as CSV text in \"csv\" instead."
},
"columnsToKeep": {
"type": "array",
"items": {
"type": "string"
},
"description": "Keep only these columns (flattened names). Takes priority over columnsToRemove."
},
"columnRenameMap": {
"anyOf": [
{
"type": "array",
"items": {
"type": "string"
}
},
{
"type": "object",
"additionalProperties": {
"type": "string"
}
}
],
"description": "Rename columns after keep/remove, as [\"oldName:newName\"] or {\"oldName\":\"newName\"}, for example {\"Details_founded\":\"founded\"}."
},
"columnsToRemove": {
"type": "array",
"items": {
"type": "string"
},
"description": "Drop these columns (flattened names). Ignored if columnsToKeep is set."
},
"dropEmptyFields": {
"type": "boolean",
"description": "Default false. Remove null and empty fields from each row."
},
"expandArrayField": {
"type": "string",
"description": "Optional. 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 limit."
},
"flattenSeparator": {
"type": "string",
"description": "Joins nested key paths when flattening. Default \"_\"."
},
"similarityThreshold": {
"type": "number",
"maximum": 0.99,
"minimum": 0.5,
"description": "Fuzzy mode only. 0.5 to 0.99, default 0.9. Higher is stricter."
}
},
"additionalProperties": false
}Prompts
Not advertised
Resources
Not advertised
90-day uptime
A lightweight connection check about every six hours, sampled on hosts with many listings. It shows the server answered, not that its tools work.
- 2026-11-07: 1 of 1 checks answered
30-day availability
Aggregated from read-only remote checks; this is not a tool-execution or security guarantee.
- Successful checks
- 1 of 1 (100%)
- Average latency
- 302 ms
- 95th percentile latency
- 302 ms
Maintenance history
Public check and source-refresh events. Editorial and ownership records remain private.
- · probe · passed · 302 ms · metadata changed · 2 tool(s)
Connect from your client
Each snippet registers the same endpoint; pick the client you use.
Claude Code
claude mcp add --transport http dataset-cleaner-exporter-mcp https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpCodex
codex mcp add dataset-cleaner-exporter-mcp --url https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpCursor
{
"mcpServers": {
"dataset-cleaner-exporter-mcp": {
"url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
}
}
}Cline
{
"mcpServers": {
"dataset-cleaner-exporter-mcp": {
"type": "streamableHttp",
"url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp",
"disabled": false
}
}
}VS Code
{
"servers": {
"dataset-cleaner-exporter-mcp": {
"type": "http",
"url": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
}
}
}Gemini CLI
gemini mcp add --transport http dataset-cleaner-exporter-mcp https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpClaude Desktop
https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpWindsurf
{
"mcpServers": {
"dataset-cleaner-exporter-mcp": {
"serverUrl": "https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp"
}
}
}Let your agent find its tools
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