jdatamunch-mcp
Active·★ 82·NOASSERTION·Updated 2026-10-21
jDataMunch is an MCP server designed to help AI agents and analysts query large tabular datasets like CSV, Excel, and Parquet files without overwhelming the LLM's context window. It profiles data locally, enabling server-side filtering, aggregation, and joining, drastically reducing token usage and improving query efficiency for large files.
#Tabular Data#AI Agent Tool#LLM Context Reduction#Data Retrieval#Data Profiling#Local-first#MCP Protocol
01
Features
01Profile tabular datasets (columns, types, cardinality, null rates, distributions)
02Query data with server-side filters, aggregations, and joins
03Integrate with AI agents via MCP for efficient data retrieval
04Reduce LLM token consumption by avoiding raw data pasting
05Identify data quality issues and preflight schema changes
02
Compatibility
Python
Runtime
Verified via docs
03
Quick start
1
$ pipx install "jdatamunch-mcp[excel,parquet]"
04
Use cases
↳AI agents exploring and understanding large unseen datasets
↳Analysts performing server-side aggregations and filters on millions of rows
↳Integrating tabular data insights into LLM context without exceeding token limits
↳Detecting data quality issues and schema drift in data pipelines
05
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