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Techniques and Tools for Data Analysis, Exploration, and Working with Parquet and CSV Files MCP tools

Production-ready MCP servers that extend AI capabilities through file access, database connections, APIs, and contextual services.

68,953 tools. Last updated 2026-02-04 23:06
  • Execute SQL queries on CSV and Parquet data sources using DuckDB syntax to retrieve structured results for data analysis and visualization.
    MIT
  • Load and analyze data files from local paths or URLs in formats like CSV, JSON, Excel, and Parquet to extract DataFrame information and metadata for data understanding.
    Apache 2.0
  • Create bar charts from SQL query results on CSV, Parquet, or database sources to visualize data relationships and trends for analysis.
    MIT
  • Create histogram visualizations from SQL query results on CSV, Parquet, or database sources. Generate distribution plots for data analysis and business intelligence.
    MIT
  • Execute SQL queries on CSV or Parquet sources using DuckDB syntax via the Zaturn MCP server, returning results as a dataframe for analysis and visualization.
    MIT
  • Create scatter plots from SQL query results on CSV or Parquet data sources to visualize relationships between variables for data analysis.
    MIT

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