Csv AI Agent Skills

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

An MCP server that executes SQL via ConnectorX and streams the result to CSV or Parquet in PyArrow RecordBatch chunks. Output formats: csv or parquet CSV: UTF-8, header row is always written Parquet: PyArrow defaults; schema mismatch across batches raises an error Return value: the string "OK" on success, or "Error: " on failure On failure the partially written output file is deleted CSV token cou

Anyquery is a SQL query engine that allows you to run SQL queries on pretty much anything. It supports querying files, databases, and apps (e.g. Apple Notes, Notion, Chrome, Todoist, etc.). It's built on top of SQLite and uses plugins to extend its functionality. It can also connect to LLMs (e.g. ChatGPT, Claude, Cursor, TypingMind, etc.) to allow them to access your data. Finally, it can act as a

Zaturn: Your Co-Pilot For Data Analytics & Business Insights Zaturn provides tools that enable AI models to run SQL, so you don't have to. It can be used as an MCP or as a web interface similar to Jupyter Notebook. Zaturn can currently connect to the following data sources: - SQL Databases: PostgreSQL, SQLite, DuckDB, MySQL, ClickHouse, SQL Server, BigQuery - Files: CSV, Parquet Request data sourc

A mcp server that bridges Dune Analytics data to AI agents. - getlatestresult: Fetch the latest results of a Dune query by ID. - runquery: Execute a Dune query by ID and retrieve results. - CSV Output: All results are returned as CSV-formatted strings for easy processing. - Python 3.10+ - A valid Dune Analytics API key (get one from Dune Analytics) To install Dune Analytics for Claude Desktop auto

A powerful Microsoft SQL Server MCP (Model Context Protocol) server that enables Claude Desktop to interact with SQL Server databases through natural language queries. - 🤖 AI-Ready: Seamless integration with Claude Desktop and MCP protocol - 🔍 Smart Queries: Execute SQL queries in CSV or JSON format through natural language - 🔐 Secure Authentication: Support for SQL Server Auth, Windows Auth, a

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters).

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas