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Import Check: Validate & Clean CSV

io.github.LeBorgneAntoine/import-checkVersion 0.2.0

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

Status

Responds151 msAnswered our handshake without sign-in.

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Last checked
Nov 14, 2026, 14:39 UTC
Latency
151 ms
Remotes responding
1 of 1
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Hosting
Hosted outside the EU (detected)
Registry data as of
Nov 14, 2026, 22:14 UTC

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Connect

Streamable HTTP
https://check.orvel.dev/mcpResponds151 ms
No sign-in

Claude Code

claude mcp add --transport http import-check https://check.orvel.dev/mcp

Claude Desktop and claude.ai

Settings > Connectors > Add custom connector
Name: import-check
Remote MCP server URL: https://check.orvel.dev/mcp

Cursor

{
  "mcpServers": {
    "import-check": {
      "url": "https://check.orvel.dev/mcp"
    }
  }
}

VS Code

code --add-mcp '{"name":"import-check","type":"http","url":"https://check.orvel.dev/mcp"}'

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Tools

10 tools

Tools of Import Check: Validate & Clean CSV
Read-only
Idempotent
Open world
clean_csvApply 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.NoNoNoNo
get_csv_exampleReturn a fixed synthetic CSV and its column schema. Free, no key or quota. Copy the structure, then supply your own CSV to validate_csv.NoYesYesNo
get_csv_usageRead remaining operations and expiry for the API key supplied in the Authorization header. Does not consume credit.NoYesYesNo
get_table_exampleReturn 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.NoYesYesNo
inspect_tableProfile 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.NoNoNoNo
prepare_tableSelect, 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.NoNoNoNo
reconcile_tablesJoin 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.NoNoNoNo
validate_csvCheck 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.NoNoNoNo
view_csv_demoValidate 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.NoYesYesNo
view_table_demoJoin 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.NoYesYesNo

Details

Registry status
Active
Published
Oct 1, 2026
Updated
Oct 1, 2026
Repository
Not given
Categories (suggested)
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GDPR
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