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Query CSV and Excel files with read-only SQL using DuckDB.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-tabular" yet — see the docs or source repo.
Load ./sales.xlsx, inspect the schema first, then run a SQL query to get total sales by region and return the top 10 rows ordered by total descending.
Returns workbook or table schema details and a result table with sales aggregated by region.
Load ./customers.csv, list available columns and their data types, and identify which fields are suitable for filtering or grouping.
Returns the CSV column list, data types, and notes on key fields useful for analysis.
After loading ./inventory.csv, query items with stock below 20 and status = active, returning product name, SKU, and stock quantity.
Returns a table of matching records without modifying the source file.
Data analysts or researchers can run SQL directly on CSV and Excel files for quick filtering, aggregation, and result inspection. It is useful for ad hoc analysis of local tabular data.
Developers working with unfamiliar data files can inspect schema and types before writing queries, reducing trial and error. This makes it easier to understand the table contents.
When you only need to read and analyze file contents without changing source data, this tool supports inspection and reporting through read-only SQL queries. It is suitable for data review and validation.
It provides SQL querying over CSV and Excel files using DuckDB. You can load files, inspect schemas, and run read-only queries.
The provided information explicitly mentions support for CSV and Excel files. For specific extensions or compatibility details, see the source repository.
The description says it runs read-only queries, so it is intended for reading, inspecting, and analyzing data rather than writing back to files. For more behavior details, see the source repository.
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