An MCP server that enables the analysis of CSV and Parquet files by providing tools for statistical summaries, data previews, and structure exploration. It allows users to query local datasets and create sample data using natural language.
Zero-dependency MCP server and CLI for token-efficient inspection of local CSV/JSON/JSONL files, providing schema, samples, and paginated filtered queries to AI agents.
MCP server for tabular data retrieval that indexes local CSV, Excel, Parquet, and JSONL files once and answers questions via column profiles, filtered rows, server-side aggregations, and joins, drastically reducing token usage for large datasets.
An MCP server that enables AI assistants to load, query, and analyze local CSV files using tools for filtering, aggregation, and grouping. It provides capabilities to describe schemas, calculate statistics, and sample data directly from CSV files.
An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.
An MCP server that lets AI assistants read and visually analyze local documents — PDFs, Excel spreadsheets, CSV files, Word documents, PowerPoint presentations, and images.
