MCP For Claude Marketplace
CSV Structural Scan and Deduplicator Alternative

CSV Structural Scan and Deduplicator Alternative MCP Connector for Claude

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Analyze CSV structure, detect delimiters, find empty cells, and remove duplicate rows.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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The CSV Structural Scan and Deduplicator is a specialized utility for validating the structural integrity of CSV datasets. It provides deep insights into your data's health by performing frequency analysis to detect delimiters like commas, semicolons, or tabs. Use get_structural_metrics to verify if column counts are consistent across all rows, identify_empty_cells to pinpoint exact coordinates of missing data, and count_duplicate_rows to quantify redundancy. For automated cleaning, get_deduplicated_payload generates a pristine version of your dataset by stripping out all duplicate entries while maintaining the original structure.

csvparsingdeduplicationdata-integrityautomation

4 tools expose this connector's capabilities to your AI agent.

count_duplicate_rows

Counts the number of duplicate rows in a CSV

identify_empty_cells

Identifies the locations of empty cells in a CSV

get_deduplicated_payload

Returns a version of the CSV with all duplicate rows removed

get_structural_metrics

Analyzes the structure of a CSV file

See how to talk to your AI agent using CSV Structural Scan and Deduplicator Alternative.

Check the structure of this CSV: 'name,age\nAlice,30\nBob,2rab'

The detected delimiter is a comma, and the column count is 2.

Find empty cells in: 'id,value\n1,\n2,val'

An empty cell was found at row 1, column 1.

Deduplicate this CSV: 'id\n1\n1\n2'

The deduplicated content is: 'id\n1\n2'

The tool uses frequency analysis to examine common separators like commas, semicolons, and tabs. It identifies the character that most consistently maintains a predictable column count across all rows.

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