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.
Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.
A token-efficient, schema-aware MCP server that enables AI assistants to safely read, modify, query, and validate JSON, YAML, and TOML files with automatic schema detection and format conversion capabilities.
MCP server that turns coding agents into data analysts: attach CSV/Parquet/JSON/XLSX or databases, profile data, run read-only SQL, and render Vega-Lite charts as SVG files.
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.
MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.
