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 SepineTam · MCP Server · ★ 260
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-for-stata safe to install? View the security audit →
MCP-for-Stata: Integrate Stata into your agent Stata is a registered trademark of StataCorp LLC. This project is an independent community-developed tool and is not affiliated with, endorsed by, or sponsored by StataCorp LLC. <!-- mcp-name: io.github.SepineTam/mcp-for-
| Stars | 260 |
| Forks | 36 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 72.78204386313/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-18 |
| Created | 2025-03-28 |
| Platforms | claude-code, codex, mcp, python |
| Est. Tokens | ~17k |
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mcp-for-stata is A MCP server for integrating Stata into your agent loop with a safety-first design.. It is categorized as a MCP Server with 260 GitHub stars.
mcp-for-stata is primarily written in Python. It covers topics such as claude-code, claude-code-plugin, claude-code-skill.
You can find installation instructions and usage details in the mcp-for-stata GitHub repository at github.com/SepineTam/mcp-for-stata. The project has 260 stars and 36 forks, indicating an active community.
mcp-for-stata is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to mcp-for-stata on Agent Skills Hub include Awesome-Journal-Skills, hol-guard, orchestkit. 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: