How to Use the Zammad MCP in AutoGen

Q: What is the best way to search for tickets using Zammad and AutoGen?

You can set up a 'Query Agent' that uses searchtickets. Instead of just returning results, you can have a second agent debate the best criteria for the next search. This refinement loop ensures your search is as precise as possible.

Q: What data does the Zammad MCP Server touch regarding privacy? (AutoGen)

The server touches User data. The dataprivacydeleteuser tool handles user deletion via a specific Data Privacy task. AutoGen can run multiple agents to debate if and how this sensitive user record should be deleted.

Q: Does Zammad support tag management with AutoGen?

It does. You can set up an agent pair: one calls listtags to see available options, and the other uses addtag or removetag based on a debate over whether the current tags are accurate.

Q: If I need to list all groups using Zammad and AutoGen?

You can use listgroups. To make this more complex, you might have one agent listing the groups, and a second agent analyzing that list against predefined business rules before presenting the final output.

Run debates on helpdesk decisions using AutoGen with Zammad to achieve consensus on ticket handling.

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Create your Vinkius account to connect Zammad to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Zammad with AutoGen

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Consensus-Driven Ticket Resolution via AutoGen

Build a team of agents that debate how to handle a complex case. One agent might run `get_ticket` to assess the initial data, while another acts as an 'SLA Agent' that checks `list_slas` and challenges the proposed timeline. The final decision requires consensus. This multi-agent setup is perfect when the answer isn't obvious. Instead of just executing a command, your system simulates negotiation between competing viewpoints to reach the best action for the Zammad ticket.

Policy Enforcement using AutoGen

Need policy checks before changing anything? You can deploy an 'Admin Agent' that first runs `get_group` details and then has a 'Security Agent' challenge it. The Security Agent might check the user roles via `list_roles` to confirm permissions. AutoGen makes agents argue over best practices. It doesn't just execute; it deliberates. This is ideal for high-stakes actions like updating critical ticket records using `update_ticket`.

Structured User Onboarding with AutoGen

Onboarding a new user requires multiple steps, and you want confirmation at every stage. One agent can call `create_user`, while another 'Compliance Agent' verifies that the required tags are applied by running `add_tag` afterward. The process only concludes when all agents agree. This debate structure forces completeness. It ensures that after creating a user, related steps—like listing their groups (`get_group`) or setting up initial roles—are confirmed by multiple internal checks.

Setup guide

Set up Zammad MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Zammad tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Zammad_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Zammad data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Zammad_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Zammad data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zammad. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Zammad MCP in AutoGen

You can set up a 'Query Agent' that uses `search_tickets`. Instead of just returning results, you can have a second agent debate the *best* criteria for the next search. This refinement loop ensures your search is as precise as possible.

Yes. You can deploy agents to handle permission changes. For example, a 'Role Agent' checks `list_roles` and then an 'Update Agent' executes the change via `update_user`, all while debating if the role modification is appropriate.

The server touches User data. The `data_privacy_delete_user` tool handles user deletion via a specific Data Privacy task. AutoGen can run multiple agents to debate *if* and *how* this sensitive user record should be deleted.

It does. You can set up an agent pair: one calls `list_tags` to see available options, and the other uses `add_tag` or `remove_tag` based on a debate over whether the current tags are accurate.

You can use `list_groups`. To make this more complex, you might have one agent listing the groups, and a second agent analyzing that list against predefined business rules before presenting the final output.

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