How to Use the ngrok MCP in AutoGen

Q: Does the server expose my ngrok API keys to agents?

The listapikeys tool returns keys that the agents can read. Ensure your agent system has proper access controls to prevent unauthorized exposure of these credentials.

Debate your infrastructure security in AutoGen by having agents negotiate access policies via direct ngrok tool execution.

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Connect ngrok MCP to AutoGen

Create your Vinkius account to connect ngrok 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 ngrok with AutoGen

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Negotiate security through debate

Assign agents to call `list_ip_policies` and `list_ip_restrictions` to verify compliance. One agent argues for strict access, while another checks if the rules break staging. They reach consensus before you deploy. This eliminates manual review cycles for simple tunnel configurations.

Resolve tunnel conflicts

Use `list_endpoints` and `list_https_edges` to give your agents a common view of the network. When tunnels overlap, the agents debate which ones to keep. They reach a decision based on your defined priorities. The system cleans up your environment automatically.

Audit infrastructure usage

Task agents with `list_api_keys` and `list_reserved_domains` to find unused assets. They debate whether to flag or ignore specific items found in the API output. Your management agent acts on their final report. This turns passive auditing into an active cleanup process.

Setup guide

Set up ngrok 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 ngrok 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="ngrok_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You provide the tools to the agents, and they decide when to call `list_endpoints` or other methods during their conversation. They negotiate the next steps based on the tool results.

This server is read-only. Agents can only inspect policies like `list_ip_policies` to inform their debate, but they cannot change your infrastructure settings.

The MCP protocol keeps the data exchange between the server and your agents private. No external parties see your tunnel or policy information.

The framework forces them to present evidence from the tools. You see the full discussion in the logs, showing exactly how they interpreted the `list_vaults` data.

The `list_api_keys` tool returns keys that the agents can read. Ensure your agent system has proper access controls to prevent unauthorized exposure of these credentials.

Use it with your favorite AI tools

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