How to Use the Mio MCP in AutoGen

Q: How do AutoGen agents negotiate when starting a Mio voice call?

One agent can propose initiating a call using startaicall while a budget agent checks getcreditbalance. The call is only executed once both agents agree that the account has sufficient funds.

Q: Can I use AutoGen to audit active Mio MCP webhooks?

Yes. You can set up a security agent to query listwebhooks and cross-reference the active endpoints against an approved list, automatically calling deletewebhook for any unauthorized entries.

Q: How do AutoGen agents collaborate on summarizing Mio transcripts?

A retriever agent pulls the text using getcalltranscript, a writer agent drafts the summary via getcallsummary, and a critic agent compares it to the metadata from getcalldetails to verify accuracy.

Q: How do I inspect the details of a specific voice call?

You can use getcalldetails to retrieve detailed metadata about any call, including duration, timestamps, and status, allowing your agents to make informed decisions based on historical data.

Deploy AutoGen multi-agent debates to coordinate Mio voice calls, verify transcript summaries, and manage active webhooks.

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Create your Vinkius account to connect Mio 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 Mio with AutoGen

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Coordinate voice campaigns using AutoGen and this MCP Server.

AutoGen shines when multiple agents collaborate on complex tasks. You can set up an AutoGen coordinator agent that uses `list_calls` to monitor current activity, while a separate voice agent selects the perfect vocal tone from `list_available_voices` and initiates Mio calls using `start_ai_call`. This multi-agent setup prevents errors before they happen. If one AutoGen agent tries to call a number, a supervisor agent can check `get_credit_balance` first to confirm you have enough Mio funds, blocking the action if the budget is too low.

Debate and refine Mio call summaries with AutoGen.

Single-agent summaries can miss critical context. With AutoGen, a transcription agent can retrieve the raw text using `get_call_transcript`, a summary agent generates an initial report with `get_call_summary`, and a critic agent challenges the output against the raw details from `get_call_details`. The AutoGen agents debate until they reach a consensus on the final Mio summary. This process guarantees that your meeting notes and action items are highly accurate before they get saved or sent to your team.

Manage Mio webhook configurations through AutoGen consensus.

Automation shouldn't mean losing control of your endpoints. You can run an AutoGen security agent that calls `list_webhooks` to audit your active listeners over this MCP server, while an integration agent uses `create_webhook` to add new notification channels as needed. If the AutoGen security agent detects an unauthorized or obsolete endpoint, it can negotiate with the integration agent to run `delete_webhook`. This keeps your Mio notification infrastructure clean and secure without manual oversight.

Setup guide

Set up Mio 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 Mio 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="Mio_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Mio MCP in AutoGen

One agent can propose initiating a call using `start_ai_call` while a budget agent checks `get_credit_balance`. The call is only executed once both agents agree that the account has sufficient funds.

Yes. You can set up a security agent to query `list_webhooks` and cross-reference the active endpoints against an approved list, automatically calling `delete_webhook` for any unauthorized entries.

A retriever agent pulls the text using `get_call_transcript`, a writer agent drafts the summary via `get_call_summary`, and a critic agent compares it to the metadata from `get_call_details` to verify accuracy.

You can use `get_call_details` to retrieve detailed metadata about any call, including duration, timestamps, and status, allowing your agents to make informed decisions based on historical data.

We isolate all API traffic within secure, zero-trust V8 execution environments. Your voice calls, generated transcripts, and webhook endpoints are handled in memory and never written to persistent logs, protecting your enterprise data from exposure.

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