How to Use the Better Stack MCP in AutoGen

Q: How do AutoGen agents access the Better Stack MCP Server?

You register the server's tools with your AssistantAgent using the AutoGen MCP extension. The agents can then call tools like listmonitors during their conversations.

Q: Can AutoGen agents delete monitors in Better Stack?

Yes, agents can execute deletemonitor if you grant them access. To prevent accidents, you can set up a human-in-the-loop proxy agent to approve any deletion requests.

Q: How does AutoGen handle conflicting data from Better Stack?

If listincidents shows an outage but liststatuspages shows everything green, your agents will debate the discrepancy. They can query getmonitor to resolve the conflict before alerting your team.

Q: Is my Better Stack infrastructure data safe with AutoGen and MCP?

Absolutely. All tool executions, including listheartbeats and listoncalls, run within an ephemeral, isolated V8 sandbox. Your raw monitoring data is never used to train public models.

Let your AutoGen agents debate incident severity and coordinate Better Stack on-call schedules.

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Create your Vinkius account to connect Better Stack 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 Better Stack with AutoGen

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Let AutoGen agents coordinate incident triage

By connecting this MCP Server, your triaging agent can fetch an incident using `get_incident` while a separate operations agent checks `list_on_calls`. They debate the best escalation path before taking action. This collaborative loop ensures no one gets paged by mistake. The agents verify the incident severity against your status page using `list_status_pages` before escalating.

Automated monitor management via agent consensus

When deploying new services, your development agent can propose a new uptime check using `create_monitor`. A security agent reviews the parameters and uses `update_monitor` to tweak the settings if they do not meet standards. This multi-agent review prevents misconfigured endpoints from slipping into production. You get a built-in audit trail of how your team's agents configured your Better Stack checks.

Resolve heartbeat failures through collaborative debugging

If a heartbeat fails, an agent queries `list_heartbeats` to identify the culprit. It passes this data to a developer agent to inspect the corresponding codebase for silent failures. Once the fix is deployed, a verification agent checks the heartbeat status again. The agents only close the discussion when the tool confirms the heartbeat is back online.

Setup guide

Set up Better Stack 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 Better Stack 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="Better Stack_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You register the server's tools with your `AssistantAgent` using the AutoGen MCP extension. The agents can then call tools like `list_monitors` during their conversations.

Yes, agents can execute `delete_monitor` if you grant them access. To prevent accidents, you can set up a human-in-the-loop proxy agent to approve any deletion requests.

If `list_incidents` shows an outage but `list_status_pages` shows everything green, your agents will debate the discrepancy. They can query `get_monitor` to resolve the conflict before alerting your team.

This integration uses the Streamable HTTP transport protocol. It allows your AutoGen agents to connect securely to the Vinkius-hosted endpoint with minimal latency.

Absolutely. All tool executions, including `list_heartbeats` and `list_on_calls`, run within an ephemeral, isolated V8 sandbox. Your raw monitoring data is never used to train public models.

Use it with your favorite AI tools

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

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Pydantic AI sdk-python

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