How to Use the zrok (Open-Source Tunnel) MCP in AutoGen

Q: How is authentication handled with zrok (Open-Source Tunnel) in AutoGen?

The initial loginaccount call provides a token that all subsequent agents reference. This ensures every decision made by the group has valid, authenticated context.

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Connect zrok (Open-Source Tunnel) MCP to AutoGen

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Setup zrok (Open-Source Tunnel) with AutoGen

Ask AI about this MCP

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Perplexity

Negotiating Resource Access

Multiple agents can discuss resource needs. One agent might call `get_account` to check available limits, while another calls `create_share` to propose a connection. They then debate if the action is allowed before converging on a decision.

Validating Tunnel Status

A security agent can call `list_environments` and flag any disabled services. A performance agent might then decide that calling `enable_environment` is necessary to proceed, forcing deliberation between competing states.

Coordinating Resource Lifecycle

The system needs consensus on whether a resource is needed. Agents can cycle through checking status with `get_share`, proposing deletion via `delete_share`, and finally confirming the clean-up, making the answer complex.

Setup guide

Set up zrok (Open-Source Tunnel) 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 zrok (Open-Source Tunnel) 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="zrok (Open-Source Tunnel)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent zrok (Open-Source Tunnel) 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="zrok (Open-Source Tunnel)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent zrok (Open-Source Tunnel) 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 zrok. 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 zrok (Open-Source Tunnel) MCP in AutoGen

AutoGen lets different agents debate which tool to use. For example, one agent suggests calling `list_shares`, and another challenges it by suggesting a pre-check with `get_account`. The consensus determines the final action.

Yes. You build systems where multiple perspectives are needed. Agents can negotiate around making a new tunnel available by calling `create_share` only after passing several internal checks.

The server provides account details and environment statuses. This structured output allows agents to debate facts, ensuring decisions are based on verifiable tool outputs rather than assumptions.

The initial `login_account` call provides a token that all subsequent agents reference. This ensures every decision made by the group has valid, authenticated context.

This server manages share configurations, environment status, and account limits. The specific data type touched is `Account Details` as well as resource definitions like active shares.

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