Chroma’s official MCP server: vector search and collection management for RAG workflows.
Nothing to run from here
Dataset Cleaner & Exporter is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
2
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Dedupe, flatten and clean messy JSON rows (emails, phones, URLs, HTML) in one call, as JSON or CSV.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http dataset-cleaner-exporter-mcp https://dataset-cleaner-exporter.nerolabs.workers.dev/mcp
# 2 — ask your agent for something these tools do
# list_capabilities, clean_rows
Dataset Cleaner & Exporter costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
NEAll 59 servers
Nero-Engine59 servers
15 categories
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http dataset-cleaner-exporter-mcp https://dataset-cleaner-exporter.nerolabs.workers.dev/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
2 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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.
No parameter schema on file.
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 int
| Parameter | Type | Required | Notes |
|---|---|---|---|
| rows | array | yes | The rows to clean. Each row is a JSON object; keys may differ between rows and values may be nested. |
| dedupMode | string | no | 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 s |
| dedupKeys | array | no | 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 k |
| keepStrategy | string | no | Which duplicate survives: most_complete (default, fewest empty fields), first or last. |
| similarityThreshold | number | no | Fuzzy mode only. 0.5 to 0.99, default 0.9. Higher is stricter. |
| flatten | boolean | no | Default true. Turn nested objects into flat columns. Arrays become one JSON-text cell. |
| flattenSeparator | string | no | Joins nested key paths when flattening. Default "_". |
| expandArrayField | string | no | 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 lim |
| cleanFields | boolean | no | Default true. Normalize emails, phone numbers and URLs, detected by field name or value shape. |
| stripHtml | boolean | no | Default false. Remove HTML tags and decode common entities in text. |
| coerceTypes | boolean | no | Default false. Turn "42" into 42 and "true" into true. Leading-zero values like "007" stay text. |
| emptyToNull | boolean | no | Default true. Blank text becomes null. |
| dropEmptyFields | boolean | no | Default false. Remove null and empty fields from each row. |
| columnsToKeep | array | no | Keep only these columns (flattened names). Takes priority over columnsToRemove. |
| columnsToRemove | array | no | Drop these columns (flattened names). Ignored if columnsToKeep is set. |
| columnRenameMap | no | Rename columns after keep/remove, as ["oldName:newName"] or {"oldName":"newName"}, for example {"Details_founded":"founded"}. | |
| maxItems | integer | no | Optional cap: read at most this many rows and return at most this many. 0 (default) means no cap. |
| outputFormat | string | no | json (default) returns rows; csv returns the same result as CSV text in "csv" instead. |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Dataset Cleaner & Exporter or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither: the repository linked on this page is where this record was collected from, not a copy of what the address serves, so it is not graded in its place. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 0.1.0.
0.1.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Dataset Cleaner & Exporter can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.