How to Use the Gotify MCP in AutoGen

Q: How do agents use Gotify for consensus?

Agents share the output of getmessages to discuss system health. They reach a group decision on whether to trigger an automated response.

Enable multi-agent debate over Gotify notification strategies using AutoGen's collaborative framework.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Gotify MCP to AutoGen

Create your Vinkius account to connect Gotify 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.

GDPR Free for Subscribers

Setup Gotify with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate Gotify notifications in AutoGen

Deploy an agent to call `send_message` while another monitors for errors. They debate the priority of alerts before committing to a dispatch. This prevents redundant notifications. The agents negotiate which priority level is appropriate for the system state.

Control Gotify applications with AutoGen

Agents use `get_applications` to verify configuration before making changes. They coordinate updates using `update_application` to ensure consistency. This removes manual oversight from your application management. The agents reach a consensus on configuration changes before executing them.

Audit this MCP Server via AutoGen

Task your agents with running `get_users` and `get_clients` to perform security audits. They check for unauthorized access points in your notification registry. This MCP Server provides the raw data for your agents to challenge each other's security assumptions. It creates a robust review loop.

Setup guide

Set up Gotify 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 Gotify 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="Gotify_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Gotify 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 Gotify. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Gotify now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Gotify MCP in AutoGen

Yes, you can assign different Gotify tool capabilities to separate agents. They will communicate to decide which one handles a specific message request.

Agents share the output of `get_messages` to discuss system health. They reach a group decision on whether to trigger an automated response.

It provides the tools needed for agents to perform actions. The logic for debate and negotiation lives within your AutoGen agent configuration.

Keep your tokens in a secure environment variable. Your AutoGen agents access these through the MCP server interface without exposing them in chat.

The message logs are only available to agents authorized to call the tools. Your notification history remains isolated within the server's control.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.