How to Use the BasicOps MCP in AutoGen

Q: How do AutoGen agents collaborate on a BasicOps task?

One agent calls gettask to analyze the details, then shares those findings in the group chat. Another agent reviews the notes and uses updatetask to log the final team decision.

Q: Can I limit which AutoGen agents can write to BasicOps?

Yes. Register the write tools like createtask only with your coordinator agent, while leaving other agents with read-only tools like listprojects.

Q: How do I register the BasicOps schema with AutoGen?

You use the mcpservertools helper with our secure HTTP transport. The adapter automatically translates the MCP schema into the format AutoGen agents expect.

Deploy AutoGen agents that debate project priorities, assign tasks, and manage your BasicOps workspace autonomously.

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Setup BasicOps with AutoGen

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Multi-agent debate over task assignment

The `list_team_users` tool lets your agent cluster analyze who has the bandwidth for new work. One agent proposes an owner, while another checks their current load, debating until they agree on the best teammate. Once they reach a consensus, they call `create_task` to assign the work. This keeps your team from getting overloaded by automated assignments.

Automated project kickoff via MCP Server

The `create_project` tool is triggered when your product agent and engineering agent agree a new initiative is ready. They debate the scope, map out the phases, and write the project directly to your workspace. They then use `list_project_sections` to build out the required columns. By using this MCP Server, your agents coordinate the entire setup phase without human intervention.

Intelligent webhook monitoring and triage

The `list_webhooks` tool lets your quality assurance agents monitor system events in real time. When an event fires, the agents debate the severity before deciding if a ticket needs escalation. If they agree it is critical, they call `update_task` to bump the priority. You get an active system that triages issues based on logical consensus.

Setup guide

Set up BasicOps 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 BasicOps 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="BasicOps_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about BasicOps MCP in AutoGen

One agent calls `get_task` to analyze the details, then shares those findings in the group chat. Another agent reviews the notes and uses `update_task` to log the final team decision.

Yes. Register the write tools like `create_task` only with your coordinator agent, while leaving other agents with read-only tools like `list_projects`.

You use the `mcp_server_tools` helper with our secure HTTP transport. The adapter automatically translates the MCP schema into the format AutoGen agents expect.

The conversation continues until your configured termination condition is met or they reach consensus. No tools are executed until the acting agent receives approval from the group.

No. The conversation logs and the data retrieved from your projects remain entirely within your local AutoGen runtime. Our hosted MCP Server only acts as a secure pipe to pass the requested data.

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