How to Use the FireHydrant MCP in AutoGen

Q: How do AutoGen agents collaborate on a FireHydrant incident?

You can register the server's tools with an AutoGen AssistantAgent. One agent can fetch state using getincident, while another analyzes the data and uses updateincident to adjust severity based on their collective decision.

Q: How do I register this MCP Server with AutoGen?

Use the autogen-extmcp extension to import the tools. This automatically maps the server's schemas so your agents can call createincident and addincidentnote directly during conversations.

Q: Can AutoGen agents track deployment changes during an outage?

Yes, agents can query listchangeevents to correlate recent code deployments with active incidents, helping the team quickly identify the commit that broke the build.

Deploy AutoGen agent teams to debate, triage, and resolve FireHydrant incidents through consensus-driven workflows.

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Create your Vinkius account to connect FireHydrant 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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Multi-agent triage with AutoGen and this MCP Server

Let specialized agents negotiate your outage response using this MCP server. An on-call AutoGen agent can detect an alert, while a security agent checks `list_change_events` to see if a recent firewall change caused it. They debate the root cause before calling `create_incident` with a unified summary. This consensus-driven approach prevents false alarms and duplicate tickets. By requiring agreement before executing `update_incident`, your team avoids noisy notification channels.

Coordinate responder teams and runbooks via debate

When an incident is active, an AutoGen coordinator agent can query `list_teams` and `list_runbooks` to find the best responders and mitigation plans. A separate safety agent reviews the proposed runbook to ensure it won't cause further degradation. Once they agree on the path forward, the coordinator agent uses `add_incident_note` to log the approved plan. Every automated action is fully vetted by multiple agent perspectives before execution.

Automated incident post-mortems and reviews

After an incident is resolved, your AutoGen agents can collaborate to write the post-mortem. One agent pulls the timeline using `get_incident`, while another gathers service context via `get_service`. They compile these facts to draft a retrospective, which is then logged via `list_retrospectives`. Automating the most tedious part of SRE work keeps your technical records highly accurate.

Setup guide

Set up FireHydrant 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 FireHydrant 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="FireHydrant_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent FireHydrant 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="FireHydrant_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent FireHydrant 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 FireHydrant. 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 FireHydrant MCP in AutoGen

You can register the server's tools with an AutoGen `AssistantAgent`. One agent can fetch state using `get_incident`, while another analyzes the data and uses `update_incident` to adjust severity based on their collective decision.

Yes, you can set up a multi-agent workflow where a coordinator agent proposes a runbook from `list_runbooks`, and a validator agent checks service health via `get_service` before authorizing the execution.

Use the `autogen-ext[mcp]` extension to import the tools. This automatically maps the server's schemas so your agents can call `create_incident` and `add_incident_note` directly during conversations.

Yes, agents can query `list_change_events` to correlate recent code deployments with active incidents, helping the team quickly identify the commit that broke the build.

The server accesses incident details, service catalogs, and team schedules. All API interactions are executed within a secure, ephemeral sandbox, meaning your operational metadata is never cached or leaked outside your runtime.

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