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134,564 tools. Last updated 2026-05-23 09:59

"Information about Parquet" matching MCP tools:

  • Create polar line plots from SQL queries on CSV or Parquet data sources. Visualize radial and angular coordinates with optional color coding for multi-dimensional analysis.
    MIT
  • Create box plots from SQL query results on CSV or Parquet data sources to visualize statistical distributions and identify outliers in your data.
    MIT
  • Load and analyze local or remote data files by providing an absolute path or URL. Supports CSV, JSON, HTML, Excel, ODS, and Parquet formats. Returns DataFrame structure and metadata for quick data understanding.
  • Visualize data distribution patterns by creating a 2D histogram from SQL query results. Generate density heatmaps for CSV and Parquet data sources to analyze spatial relationships and concentration areas.
    MIT

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  • Create bar charts from SQL query results on CSV, Parquet, or database sources to visualize data relationships and trends for analysis.
    MIT
  • Execute SQL queries on CSV and Parquet data sources using DuckDB syntax to retrieve structured results for data analysis and visualization.
    MIT
  • Retrieve schema and information about a Redis search index, including fields and attributes, to support troubleshooting and optimization.
    MIT
  • Retrieve detailed information about a Postman environment using its environment ID.
    Apache 2.0
  • Create strip plots from SQL queries on CSV or Parquet data sources to visualize relationships between variables with optional color coding for additional dimensions.
    MIT
  • Create histogram visualizations from SQL query results on CSV, Parquet, or database sources. Generate distribution plots for data analysis and business intelligence.
    MIT
  • Retrieve complete information about a specific tool, including all details about its input schema and purpose.
    MIT
  • Download the consolidated meta model for CrowdCent prediction challenges to a specified .parquet file path, enabling access to challenge data structures.
    MIT
  • Create scatter plots from SQL query results on CSV or Parquet data sources to visualize relationships between variables for data analysis.
    MIT
  • Visualize SQL query results as line charts from CSV, Parquet, or database sources to analyze trends and patterns in data.
    MIT