Data Parser MCP Server

Example Use Cases

• 1

  Load and preprocess CSV files (including date parsing and custom separators) into memory for downstream analysis.

• 2

  Answer natural-language questions about datasets (means, medians, correlations, missing values, outliers, and temporal trends).

• 3

  Generate JSON-formatted chart data (bar, line, scatter, heatmap, boxplot, histogram) with grouping and customization options for visualization pipelines.

Description

This MCP server provides CSV data ingestion with configurable parsing and automatic column type detection, stores dataset metadata, and supports a broad set of analyses (statistical, temporal, correlation, categorical, and data-quality checks). Agents can query datasets in natural language to get summaries, statistics, distributions, and outlier detection, and can request visualizations (bar, line, scatter, pie, heatmap, boxplot, histogram) returned in a JSON-friendly format. It integrates with Claude Desktop via an MCP entry and includes examples for loading, analyzing, and rendering charts programmatically.