No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by jgravelle · MCP Server · ★ 81
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is jdatamunch-mcp safe to install? View the security audit →
jDataMunch MCP: Tabular Data Retrieval for AI Agents jDataMunch is an MCP server for coding agents and analysts that answers questions about CSV, Excel, Parquet, and JSONL files without pasting the rows into the context window. Index a dataset once, then retrieve column profiles, filtered rows, server-side aggregations, and cross-dataset joins — so a million-row file costs thousands of tokens instead of millions. Install · Quickstart · Benchmarks · Commercial licensing Free for personal use. Commercial use requires a paid license — terms below. Why jDataMunch? The problem. The default way an agent explores a spreadsheet is to paste it into the prompt. A 255 MB CSV with a million rows costs roughly 111 million tokens that way, and the model still has to reason through a million rows to answer "what columns are in here?" The mechanism.
| Stars | 81 |
| Forks | 20 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 68.9956162960755/100 |
| Last Updated | 2026-09-01 |
| Created | 2026-03-25 |
| Platforms | claude-code, cli, codex, gemini, mcp, python |
| Est. Tokens | ~16k |
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jdatamunch-mcp is Token-efficient MCP server for tabular data retrieval. Index CSV/Excel files, query rows, aggregate — 99%+ token savings vs raw file reads.. It is categorized as a MCP Server with 81 GitHub stars.
jdatamunch-mcp is primarily written in Python. It covers topics such as claude, claude-code, codex.
You can find installation instructions and usage details in the jdatamunch-mcp GitHub repository at github.com/jgravelle/jdatamunch-mcp. The project has 81 stars and 20 forks, indicating an active community.
The top alternatives to jdatamunch-mcp on Agent Skills Hub include postman-mcp-server, mcp-fusion, claude-historian-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: