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Query local data files with SQL to give AI grounded answers.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Pipetable" yet — see the docs or source repo.
Use Pipetable to query ./data/sales_2024.csv, summarize revenue, order count, and average order value by month, and identify the top three months by revenue.
Returns executable SQL-backed results with monthly summaries and the top revenue months.
Use Pipetable to query ./logs/events.json, count each error type over the last 7 days, and list the fastest-growing errors.
Outputs JSON-based statistics that help identify recent error trends.
Use Pipetable to query ./warehouse/orders.parquet and ./warehouse/customers.tsv together, find orders without matching customer records, and count them.
Returns cross-file join results highlighting missing or inconsistent records.
Query CSV and TSV data with natural language and cell-level citations.
Query CSV and Excel files with read-only SQL using DuckDB.
Query CSV, Parquet, and JSON files in one folder using SQL.
Query Excel and CSV data in natural language for fast analysis.
A persistent DuckDB MCP server lets AI assistants query CSV, Parquet, and cloud data in natural language.
Query, clean, join, profile, and convert tabular data with DuckDB over MCP.