zabbix-mcp-server — security grade SAFE, quality 77/100

Security audit verdict: SAFE · quality 77/100

Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by initMAX · MCP Server · ★ 199

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

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About zabbix-mcp-server

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Quick Facts

Stars199
Forks38
LanguagePython
CategoryMCP Server
LicenseAGPL-3.0
Quality Score76.8716891958848/100
Open Issues12
Last Updated2026-08-07
Created2026-03-29
Platformsclaude-code, cli, codex, mcp, python, vscode
Est. Tokens~20k

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Frequently Asked Questions

What is zabbix-mcp-server?

zabbix-mcp-server is MCP server for the complete Zabbix API - 237 tools, multi-server, OAuth 2.1 + bearer auth, PDF reports, systemd ready. Works with ChatGPT, Claude, VS Code, Codex, JetBrains and any MCP client.. It is categorized as a MCP Server with 199 GitHub stars.

What programming language is zabbix-mcp-server written in?

zabbix-mcp-server is primarily written in Python. It covers topics such as ai-agent, ai-tools, automation.

How do I install or use zabbix-mcp-server?

You can find installation instructions and usage details in the zabbix-mcp-server GitHub repository at github.com/initMAX/zabbix-mcp-server. The project has 199 stars and 38 forks, indicating an active community.

What license does zabbix-mcp-server use?

zabbix-mcp-server is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to zabbix-mcp-server?

The top alternatives to zabbix-mcp-server on Agent Skills Hub include Overture, postman-mcp-server, notion-mcp-server. 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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