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.
Visualize SQL query results as line plots on Zaturn. Input source ID, query, and axis columns; generate plots directly from CSV or Parquet data sources using DuckDB SQL syntax.
Analyze and visualize data distributions by generating histograms from SQL queries on CSV or Parquet sources using DuckDB syntax. Ideal for exploring columnar data patterns with optional color grouping and bin customization.
Visualize data distribution by creating box plots from SQL queries on CSV or Parquet sources using DuckDB syntax. Specify x and y-axis columns, and optionally add color to represent additional dimensions.
Generate example SQL queries for blockchain datasets using DuckDB. Streamline querying and schema inspection for Ethereum data with workflow tips. Enhance efficiency in blockchain data analysis.
Remove specified entities and their related connections from the knowledge graph stored in the MCP DuckDB Memory Server, ensuring efficient data management.
A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis.
A Model Context Protocol server implementation that connects AI assistants to DuckDB, enabling them to query and analyze data from various sources including CSV, Parquet, JSON, and cloud storage through SQL.
An MCP server that enables RAG (Retrieval-Augmented Generation) on markdown documents by converting them to embedding vectors and performing vector search using DuckDB.