How to Use the Deskpro MCP in AutoGen

Q: Will AutoGen agents automatically close my Deskpro tickets?

Only if you program them to do so. They can use updateticketproperties to change a status to closed, but you control the consensus rules that allow that action.

Let AutoGen debate and resolve Deskpro support tickets through multi-agent consensus.

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Connect Deskpro MCP to AutoGen

Create your Vinkius account to connect Deskpro 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 Deskpro with AutoGen

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Perplexity

Agents debate Deskpro tickets

Complex support requests rarely have obvious answers. You can assign one AutoGen agent to act as a security reviewer and another as a support tech. They pull the queue using `list_helpdesk_tickets` and look at pending issues. The tech might suggest a quick fix. The security agent pushes back if the request violates policy. They argue until they reach consensus, at which point one of them calls `update_ticket_properties` to apply the agreed-upon fix.

Draft responses via AutoGen consensus

Writing public documentation requires review. One agent drafts a response to a known bug. A second agent calls `list_kb_articles` to see if that advice contradicts existing manuals. If they find a conflict, they pull the exact text with `get_article_content` and rewrite the draft. Once both agents approve the final version, they fire off `create_new_helpdesk_ticket` to submit the draft for human review.

Monitor the Deskpro MCP Server

System outages cause panic. You can build a watcher agent that periodically checks your helpdesk infrastructure. It runs `check_api_health` to verify connectivity. If the API lags, the watcher alerts an operations agent. That second bot might run `list_configured_webhooks` to see if a specific integration is causing the bottleneck. AutoGen handles the investigation while you sleep.

Setup guide

Set up Deskpro 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 Deskpro 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="Deskpro_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Deskpro_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Deskpro. 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 Deskpro MCP in AutoGen

Install the autogen-ext package with MCP support. Fetch the available functions using mcp_server_tools and pass that list directly into your AssistantAgent constructor.

Yes. You can configure a group chat where a triage bot, a tech bot, and a manager bot all read the output of get_ticket_details before deciding how to reply.

If a tool call fails, the framework feeds the error message back into the conversation. The agents can read the failure reason and try calling the endpoint again with different parameters.

Only if you program them to do so. They can use update_ticket_properties to change a status to closed, but you control the consensus rules that allow that action.

No data persists outside the immediate conversation. Vinkius routes the get_user_profile requests through an ephemeral sandbox, ensuring personal emails disappear the moment your local script terminates.

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