@mcpx-digital/csv-tools
Related Servers
Alternatives to @mcpx-digital/csv-tools
No user-submitted related servers found.
Related Servers
- FlicenseAqualityDmaintenanceEnables comprehensive CSV file management including creating, editing, analyzing, and transforming CSV data anywhere in the filesystem. Provides statistical analysis, data validation, filtering, and grouping capabilities through MCP protocol over stdio transport.15-
- FlicenseBqualityDmaintenanceEnables Claude to directly access, query, and analyze local CSV files using natural language, keeping data private and local.41-
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to analyze large CSV files locally by importing them into SQLite, profiling columns, and running read-only SQL queries without data leaving the machine.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to validate CSV exports against schemas, infer schemas from example files, profile datasets, and diff before/after exports for lab/LIMS data-quality checks.MIT
- FlicenseNot gradedqualityCmaintenanceProvides tools to inspect dataset schema, profile, preview, and execute read-only SQL queries on uploaded CSV/Excel files.-
- FlicenseNot gradedqualityAmaintenanceProvides tools to analyze local PDFs and CSVs (page count, text search, scoring, column stats) with strict refusal to guess ambiguous data. Requires a paid license.-
TDQS
Scored across 6 tools
Most tools target distinct operations (convert, sample, find duplicates, validate, schema check). However, validate_csv and schema_check overlap somewhat since both assess CSV structure/quality, though they focus on different aspects (structure vs. column requirements/types). The descriptions help distinguish them.
Five tools follow snake_case with clear verb_noun or noun patterns (json_to_csv, csv_to_json, validate_csv, sample_rows, find_duplicate_keys), but schema_check lacks a verb and uses a different construction, introducing minor inconsistency.
Six tools is well-scoped for a CSV utility server. Each tool covers a distinct common CSV task (conversion, sampling, duplication detection, validation, schema checking), earning its place without redundancy.
The surface covers key CSV operations: conversion both ways, sampling, duplicate detection, validation, and schema checking. Minor gaps include a dedicated CSV writing/transformation tool (e.g., filter columns, sort) or a dedicated row/column manipulation tool, but core workflows are well supported.