"author:jgravelle" matching MCP servers:

Lets AI agents navigate documentation by section instead of reading files by brute force, reducing token usage and improving precision.

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.

Enables transparent proxying of upstream MCP servers and OpenAI/Anthropic API calls so large tool responses are handle-ified and can be queried with universal verbs, cutting token usage while preserving access to full payloads.