Zammad MCP Server

Connect Claude, Cursor, or any MCP client to your Zammad helpdesk with a production-ready Model Context Protocol server.

Zammad MCP Server

The Zammad MCP Server is a free, open-source Model Context Protocol (MCP) bridge between AI assistants and your Zammad instance. It exposes tickets, users, organizations, and groups as typed MCP tools so agents can search, summarize, and update helpdesk data through natural language — with granular access control and safe defaults.

• License: MIT
• Package: zammad-mcp-server on PyPI
• Source: github.com/Softoft-Orga/zammad-mcp-server

Who is this for?

How this fits the Zammad + AI landscape

flowchart LR
  subgraph native [Zammad 7 native AI]
    Z7[Summaries and writing assistant inside Zammad UI]
  end
  subgraph mcp [Zammad MCP Server]
    MCP[Claude Desktop Cursor custom agents]
  end
  subgraph otai [Open Ticket AI Runtime]
    RT[Custom trained models on-prem routing]
  end
  Zammad[(Zammad REST API)]
  Z7 --> Zammad
  MCP --> Zammad
  RT --> Zammad

• Zammad 7 native AI — built-in summaries, writing assistant, and AI agents inside the Zammad UI.
• Zammad MCP Server (this project) — connects external MCP clients (Claude Desktop, Cursor, your own agents) to Zammad.
• Open Ticket AI Runtime — on-prem inference with custom-trained classification models via the OTAI Zammad connector plugin (see Zammad + OTAI integration).

All three can coexist. MCP is the fastest path to “talk to my helpdesk from Claude.”

Key features

• 30+ MCP tools for tickets, articles, users, organizations, and groups
• Access control via environment variables (category allow/deny, tool deny-list, group scope)
• Multiple auth modes — API token (recommended), OAuth2, basic auth
• Install options — pip, uvx, Docker, SSE transport for remote clients
• Built-in prompts — ticket summary, customer communication, escalation analysis
• Resource URIs — zammad://ticket/{id}, zammad://user/{id}, zammad://states

Documentation map

Learn more

• Tutorial: Zammad MCP Server — setup and usage (blog)

Next steps

1. Follow the Quick Start guide.
2. Harden access with Security before production use.
3. Need custom models trained on your queues? Explore Open Ticket AI for Zammad.