mcp-superset — security grade SAFE, quality 75/100

Security audit verdict: SAFE · quality 75/100

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 bintocher · MCP Server · ★ 57

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

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About mcp-superset

mcp-superset [![Tools: 137](https://img.shields.io/badge/MCPtools-132%2B-brightg

ai-toolsapache-supersetclaudefastmcpllmmcpmcp-servermodel-context-protocolsuperset

Quick Facts

Stars57
Forks14
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score74.9748069091756/100
Last Updated2026-09-19
Created2026-03-10
Platformsclaude-code, mcp, python
Est. Tokens~19k

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Frequently Asked Questions

What is mcp-superset?

mcp-superset is MCP server for managing Apache Superset — 128+ tools for dashboards, charts, datasets, SQL Lab, access control. It is categorized as a MCP Server with 57 GitHub stars.

What programming language is mcp-superset written in?

mcp-superset is primarily written in Python. It covers topics such as ai-tools, apache-superset, claude.

How do I install or use mcp-superset?

You can find installation instructions and usage details in the mcp-superset GitHub repository at github.com/bintocher/mcp-superset. The project has 57 stars and 14 forks, indicating an active community.

What license does mcp-superset use?

mcp-superset is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to mcp-superset?

The top alternatives to mcp-superset on Agent Skills Hub include claude-historian-mcp, youtube-connector-mcp, lc2mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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