jdatamunch-mcp: Token-efficient MCP server for tabular data retrieval

by jgravelle · MCP Server · ★ 83

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install jdatamunch-mcp

claude mcp add jdatamunch -- uvx jdatamunch-mcp
claude mcp add jdatamunch -- uvx --from "jdatamunch-mcp[excel,parquet]" jdatamunch-mcp

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

claudeclaude-codecodexcopilotcsvcursordata-analysisdata-explorationdeveloper-toolsexcel

Quick Facts

Stars83
Forks20
LanguagePython
CategoryMCP Server
Quality Score69/100
Open Issues1
Last Updated2026-11-04
Created2026-03-25
Platformsclaude-code, cli, codex, gemini, mcp, python
Est. Tokens~16k

About jdatamunch-mcp

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.

Compatible Skills

These tools work well together with jdatamunch-mcp for enhanced workflows:

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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