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Query, clean, join, profile, and convert tabular data with DuckDB over MCP.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "stagenth · 数据工具箱" MCP server from askskill: Run: claude mcp add --transport http 'com-stagenth-data-kit' 'https://stagenth.com/mcp/data-kit/'
Use this tool to read sales.csv and customers.json, join them on customer_id, and return customer name, order amount, and order date sorted by amount descending.
A joined result table with the requested fields sorted by amount in descending order.
Profile users.parquet and report each column's type, missing values, unique counts, and any potentially problematic fields.
A profiling report showing column types, missing values, uniqueness statistics, and anomaly hints.
Read events.json, remove duplicate records, filter out rows with empty timestamps, and output the result in Parquet format.
A cleaned Parquet dataset or the corresponding converted output.
When analysts or researchers need to work with CSV, JSON, and Parquet files, they can use it to query, clean, and convert data in one place.
Developers working with larger tabular datasets in an MCP environment can use server-side DuckDB to run queries and joins instead of handling files manually.
Before importing external data into an analysis workflow or application, users can profile and clean it to catch missing values, duplicates, or field issues early.
No documentation provided
Check the source repo for usage and examples.
It provides server-side DuckDB data operations over MCP, including querying, joining, profiling, cleaning, and converting CSV, JSON, and Parquet files.
The provided information explicitly mentions CSV, JSON, and Parquet. For any additional formats, see the source repository.
The description says it runs with server-side DuckDB over MCP. Specific installation steps or prerequisites are not provided, so see the source repository.
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