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local install
xlsx-for-ai
50 spreadsheet tools for .xlsx: recalc formulas, repair broken refs, read/write, diff, audit.
Tools
26
GitHub stars
5
Installs / wk
273
Licence
MIT
Transport
stdio
Last checked
never
Tools & capabilities
26 toolsRead from the published package source — this server runs locally, so there is no endpoint to query. Names are taken from the code, not observed at runtime, and descriptions are often absent.
shopify_amazon_feed
from source
shopify_collections_import
from source
shopify_ebay_feed
from source
shopify_google_feed
from source
shopify_inventory_import
from source
shopify_products_import
from source
shopify_products_import_fix
from source
shopify_ups_feed
from source
shopify_url_redirects_import
from source
xlsx_aggregate
from source
pandas-style df.groupby([cols]).agg({col: func}) on a LOCAL .xlsx file. funcs: sum / mean / min / max / count / count_distinct.\n pandas-style df.groupby([cols]).agg({col: func}) on a LOCAL .xlsx file. funcs: sum / mean / min / max / count / count_distinct.\n
xlsx_convert
from source
universal spreadsheet format converter. Reads ANY of 25+ input formats (xlsx, xlsb, xlsm, xls, ods, fods, numbers, csv, tsv, dbf, lotus 1-2-3, quattro pro, sylk, dif, html, rtf, et… universal spreadsheet format converter. Reads ANY of 25+ input formats (xlsx, xlsb, xlsm, xls, ods, fods, numbers, csv, tsv, dbf, lotus 1-2-3, quattro pro, sylk, dif, html, rtf, etc.) and emits ANY supported output format (xlsx, csv, json, md, html, etc.).\n
xlsx_describe
from source
pandas-style df.describe() per column — count, nulls, unique, min/max/mean/std for numerics, dtype with purity score.\n pandas-style df.describe() per column — count, nulls, unique, min/max/mean/std for numerics, dtype with purity score.\n
xlsx_diff
from source
compute a semantic diff between two LOCAL .xlsx files — cell-level deltas, formula changes, added/removed rows.\n compute a semantic diff between two LOCAL .xlsx files — cell-level deltas, formula changes, added/removed rows.\n
xlsx_eval
from source
evaluate Excel formulas against a LOCAL .xlsx file via HyperFormula. xlwings-style.\n evaluate Excel formulas against a LOCAL .xlsx file via HyperFormula. xlwings-style.\n
xlsx_filter
from source
pandas-style row filter on a LOCAL .xlsx file with predicates AND-combined: eq/ne/gt/gte/lt/lte/contains/in/is_null/not_null.\n pandas-style row filter on a LOCAL .xlsx file with predicates AND-combined: eq/ne/gt/gte/lt/lte/contains/in/is_null/not_null.\n
xlsx_formulas
from source
extract every formula in a LOCAL .xlsx workbook — cell coord (A1), formula text, cached result. openpyxl-style read-only metadata.\n extract every formula in a LOCAL .xlsx workbook — cell coord (A1), formula text, cached result. openpyxl-style read-only metadata.\n
xlsx_list_sheets
from source
list sheet names, dimensions, and visibility for a LOCAL .xlsx file.\n list sheet names, dimensions, and visibility for a LOCAL .xlsx file.\n
xlsx_named_ranges
from source
list all defined names (named ranges) in a LOCAL .xlsx workbook — name, scope (workbook or sheet), kind (cell / range / formula), reference.\n list all defined names (named ranges) in a LOCAL .xlsx workbook — name, scope (workbook or sheet), kind (cell / range / formula), reference.\n
xlsx_pivot
from source
pandas-style pivot_table() on a LOCAL .xlsx file — reshape a flat table into a 2D matrix where rows are unique values of pandas-style pivot_table() on a LOCAL .xlsx file — reshape a flat table into a 2D matrix where rows are unique values of
xlsx_read
from source
xfa — read an .xlsx file by path and return a rendered markdown/JSON/SQL representation.\n\n xfa — read an .xlsx file by path and return a rendered markdown/JSON/SQL representation.\n\n
xlsx_redact
from source
redact PII and sensitive values from a LOCAL .xlsx file before sharing or archiving.\n redact PII and sensitive values from a LOCAL .xlsx file before sharing or archiving.\n
xlsx_schema
from source
infer column schema of a LOCAL .xlsx file — types, nullable flags, header row, sample values.\n infer column schema of a LOCAL .xlsx file — types, nullable flags, header row, sample values.\n
xlsx_sort
from source
pandas-style df.sort_values() on a LOCAL .xlsx file with multi-column sort and per-column direction (asc/desc, default asc).\n pandas-style df.sort_values() on a LOCAL .xlsx file with multi-column sort and per-column direction (asc/desc, default asc).\n
xlsx_tables
from source
list every Excel ListObject ( list every Excel ListObject (
xlsx_value_counts
from source
pandas-style Series.value_counts() on one column of a LOCAL .xlsx file — count each unique value, sorted by frequency desc, with percentage.\n pandas-style Series.value_counts() on one column of a LOCAL .xlsx file — count each unique value, sorted by frequency desc, with percentage.\n
xlsx_write
from source