How to Use the Jira Service Management (JSM) MCP in AutoGen

Q: How do I register Jira Service Management (JSM) tools with an AutoGen agent?

Use mcpservertools with your server URL to retrieve the tool definitions. You then pass this list to the constructor of your AutoGen AssistantAgent to make tools like listrequests available.

Q: Can multiple AutoGen agents use Jira Service Management (JSM) tools simultaneously?

Yes. AutoGen agents can call tools like getrequest or listqueues during their conversational turns. The framework handles the execution sequence as the agents debate the resolution path.

Q: How do I handle schema conversion between AutoGen and JSM tools?

The McpToolAdapter in the autogen-ext package handles all schema conversion automatically. You do not need to manually map inputs or outputs for tools like listcustomers.

Let AutoGen agents debate and coordinate on Jira Service Management queues and support requests.

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Setup Jira Service Management (JSM) with AutoGen

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Coordinate triage through multi-agent debate

`list_queues` provides the raw backlog count and triage structure for your support desks. In AutoGen, your triage agent reads this list and debates priority with your scheduling agent using this MCP Server. They negotiate which tickets require immediate attention based on queue density. Once they agree on a priority queue, `list_requests` pulls the actual summaries and status codes. The agents analyze this list together, ensuring no critical ticket is overlooked during the handoff.

Analyze ticket context with specialized agents

`get_request` retrieves the complete details, including participants and custom fields, for any specific customer ticket. An AutoGen security agent can inspect these fields for sensitive data while a support agent drafts a response. They collaborate to ensure compliance before any action is taken. To verify account standing, another agent runs `list_organizations` to check the business entity. This multi-perspective analysis prevents manual errors in high-stakes support environments.

Deploy an AutoGen MCP Server agent group

`list_service_desks` fetches the full list of active portals and project keys. Your coordinator agent uses this tool to assign specific service desks to specialized sub-agents. Each sub-agent runs `list_request_types` to understand the service catalog of their assigned desk. This hierarchical setup lets you manage complex, multi-portal organizations without overloading a single agent.

Setup guide

Set up Jira Service Management (JSM) 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 Jira Service Management (JSM) 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="Jira Service Management (JSM)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Jira Service Management (JSM) 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="Jira Service Management (JSM)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Jira Service Management (JSM) 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 Jira Service Management. 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 Jira Service Management (JSM) MCP in AutoGen

Use `mcp_server_tools` with your server URL to retrieve the tool definitions. You then pass this list to the constructor of your AutoGen `AssistantAgent` to make tools like `list_requests` available.

Yes. AutoGen agents can call tools like `get_request` or `list_queues` during their conversational turns. The framework handles the execution sequence as the agents debate the resolution path.

The integration supports both stdio and Streamable HTTP transports. AutoGen's `McpToolAdapter` automatically converts the server's tool schemas into the format required by the agents.

The `McpToolAdapter` in the `autogen-ext` package handles all schema conversion automatically. You do not need to manually map inputs or outputs for tools like `list_customers`.

The MCP Server runs inside a zero-trust V8 sandbox, ensuring your organization logs, customer names, and request summaries are processed entirely in memory. All API requests are encrypted, and credentials are never stored on the platform.

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