zendesk-mcp-server: A Model Context Protocol server for Zendesk

by reminia · MCP Server · ★ 124

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

Security audit verdict: SAFE · quality 74/100

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. Full audit →

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.

mcp-serverzendesk

Quick Facts

Stars124
Forks91
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score74/100
Open Issues16
Last Updated2026-08-27
Created2024-12-16
Platformsmcp, python
Est. Tokens~7k

About zendesk-mcp-server

Zendesk MCP Server A Model Context Protocol server for Zendesk. This server provides a comprehensive integration with Zendesk. It offers: Tools for retrieving and managing Zendesk tickets and comments Specialized prompts for ticket analysis and response drafting Full access to the Zendesk Help Center articles as knowledge base Setup build: or in short.

Compatible Skills

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

  • bloodhound_mcp — semantic(0.74)+same_lang+similar_pop+shared_platform (60%)
  • plane-mcp-server — semantic(0.77)+same_lang+similar_pop+shared_platform (60%)
  • sec-edgar-mcp — semantic(0.72)+same_lang+similar_pop+shared_platform (60%)
  • kagimcp — semantic(0.61)+same_lang+similar_pop+shared_platform (56%)

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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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