Import Check: Validate & Clean CSV MCP Server

by leborgneantoine Your server? Claim it

answering

Import Check: Validate & Clean CSV is answering right now. Last checked 14 min ago. It exposes 10 tools.

Validate and prepare CSV; reconcile two tables with exact keys and full findings. Fixed free demos.

Uptime history 12 days of history · worst day 97%

12 days agonow

100.0%

Uptime 24h

182 of 182 checks

Tools

read from the server

226 ms

Response time

average over 24h

open, no key

Access

streamable-http

What changed 7

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 1 October 2026. No other catalogue keeps this.

1 Oct 5 tools appeared get_table_example, inspect_table, prepare_table and 2 more

1 Oct a tool changed version2 times that day

and 1 more, back to 1 October 2026

Import Check: Validate & Clean CSV missed 5 checks this week

Everything else answered, so this is steady rather than shaky. We check every 15 minutes, which is how a one-off gets told apart from the start of a pattern, and how you hear about the next one within the hour instead of from your users.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 14 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add import-check --transport http https://import-check-production.up.railway.app/mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "import-check": {
      "url": "https://import-check-production.up.railway.app/mcp"
    }
  }
}

~/.codex/config.toml

[mcp_servers.import-check]
url = "https://import-check-production.up.railway.app/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "import-check": {
      "url": "https://import-check-production.up.railway.app/mcp"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "import-check": {
      "url": "https://import-check-production.up.railway.app/mcp"
    }
  }
}

This server publishes 1 more address. The block above uses the one we reach during checks; the full list is under Endpoints below, and the author may intend a particular one for your client.

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

csv

get_csv_example

Return a fixed synthetic CSV and its column schema. Free, no key or quota. Copy the structure, then supply your own CSV to validate_csv.

get_csv_usage

Read remaining operations and expiry for the API key supplied in the Authorization header. Does not consume credit.

view

view_csv_demo

Validate the fixed example with the current engine. Free and no arguments; demonstrates duplicate, email, amount and date findings. Custom files require validate_csv and paid access.

view_table_demo

Join the bundled fixed tables and show changed and unmatched records. No arguments, key or credit. This cannot process custom data; use reconcile_tables with a paid key for your files.

clean

clean_csv

Apply only requested column renames and transformations, then validate the output against schema. Cleanup column names refer to the original headers; schema names refer to the renamed output. Transformations run in listed order. decimal_comma changes only plain numbers such as 12,50; ambiguous grouping stays unchanged. No records or columns are removed. Returned csv_text is UTF-8-compatible with CRLF record endings. One paid operation includes cleanup and validation. Spreadsheet-safe escaping is opt-in and may make numeric negative cells fail numeric validation; inspect the final report before import.

inspect

inspect_table

Profile a CSV or explicit string table before writing a recipe. Return empty, distinct and duplicate-value counts per column and complete formula warnings; no schema or business validity is inferred. Supply CSV OR columns/rows, never both. JSON numbers must be encoded as strings so identifiers keep leading zeros. One paid operation; no content retained. Reuse request_id only for identical input.

prepare

prepare_table

Select, rename, derive and convert columns using a caller-owned version-1 recipe. Rules reference original input headers; output follows recipe order and omitted columns are listed. All input rows remain. Any failed conversion returns valid=false, all findings and csv_text=null, never a partially transformed file. No arithmetic, arbitrary code, schema inference or destination writes. One completed report costs one operation, including valid=false. Use reconcile_tables for two-file matching.

reconcile

reconcile_tables

Join two bounded tables using exact string or composite keys. Both sides must have non-empty unique keys: duplicates block the entire output, including many-to-many matches. Choose left, inner or full retention explicitly; unmatched records are reported even if excluded. Optional compare fields flag changed values without resolving them. Output includes row lineage; missing-side fields are empty strings. No trimming, fuzzy matching or destination writes. Combined inputs share 1 MB/10,000 records/250,000 cells. One completed report costs one operation; reuse request_id for identical retries. Full findings or an uncharged size error, never silent truncation.

table

get_table_example

Return fixed synthetic left/right tables and a reusable join recipe. No arguments, key or credit. Copy the structure for reconcile_tables; mode controls which unmatched rows appear in output.

validate

validate_csv

Check a CSV against your explicit schema; return all issue counts and at most 200 detailed findings. Headers match exactly; required=false permits empty cells, not missing headers. Unique compares raw non-empty strings. Dates use YYYY-MM-DD, decimals use a dot without grouping, booleans use true/false. A valid=false report is a completed paid operation, not a tool failure. No values are changed; use clean_csv for explicit transformations. Validity covers only the supplied rules, not destination-system or business correctness.

Endpoints

URL	Transport	State	Latency	Checked
https://import-check-production.up.railway.app/mcp	streamable-http	answering	189 ms	15 min ago
https://check.orvel.dev/mcp	streamable-http	answering	182 ms	14 min ago

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Import Check: Validate & Clean CSV — questions

Answers built from our own checks of this server.

What can Import Check: Validate & Clean CSV do?

It exposes 10 tools, read directly from the server on our last check. Among them: clean_csv, get_csv_example, get_csv_usage, get_table_example, inspect_table, prepare_table and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

What is Import Check: Validate & Clean CSV mostly used for?

Its tools cluster around csv and view. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.

Is Import Check: Validate & Clean CSV working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 182 of 182 checks got a reply (100.0%), average response time 226 ms. The bar chart above shows every period we have measured.

How do I connect Import Check: Validate & Clean CSV?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Import Check: Validate & Clean CSV need an API key?

No. Import Check: Validate & Clean CSV completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Import Check: Validate & Clean CSV?

It answers our handshake in 226 ms on average, which is faster than 58% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.