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 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.
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.
Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.
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.
An MCP server that provides AI assistants with structured, type-safe access to tabular datasets from CSV files. It enables users to list, describe, and query data using filters and projections with support for hot reloading.
