How to Use the Vapi MCP in AutoGen

Q: How does AutoGen use Vapi for deliberation?

Vapi provides structured communication via createphonecall. The debate agents then analyze the resulting transcripts and metrics from getcalldetails to reach a consensus.

Q: How can I view all resources available in Vapi and AutoGen?

You run listagenttools to get a complete list of capabilities, or you use listphonenumbers if your negotiation requires checking endpoints.

Q: What happens when agents need to adjust roles using Vapi and AutoGen?

The updateassistant tool allows the controlling agent to modify an existing persona's configuration, ensuring that all participating parties are operating with the current ruleset.

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Setup Vapi with AutoGen

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Perplexity

Simulate Complex Negotiations

To simulate a debate, your agent uses `create_phone_call` to initiate communication. The multi-agent system then needs the result—the conversation's outcome. Once the call is done, running `get_call_details` provides the transcripts and metrics that all competing agents can review for consensus.

Manage Agent Roles

You set up different roles using `create_assistant`, giving each agent a distinct persona (e.g., 'Risk Officer,' 'Speed Expert'). The system uses the resulting configuration to govern their debate. If an agent needs a role change mid-conversation, you use `update_assistant` to adjust its parameters on the fly.

System Monitoring and Oversight

When multiple agents are talking, you need oversight. Use `list_squads` to see which multi-agent groups are active. You can also check system status with `list_calls`. These listing tools help the supervising agent monitor the entire negotiation process.

Setup guide

Set up Vapi 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 Vapi 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="Vapi_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Vapi MCP in AutoGen

Vapi provides structured communication via `create_phone_call`. The debate agents then analyze the resulting transcripts and metrics from `get_call_details` to reach a consensus.

Yes. Since AutoGen is built around passing information between competing agents, Vapi's clear tool definitions make it easy for multiple roles to interact with the same data.

You run `list_agent_tools` to get a complete list of capabilities, or you use `list_phone_numbers` if your negotiation requires checking endpoints.

The `update_assistant` tool allows the controlling agent to modify an existing persona's configuration, ensuring that all participating parties are operating with the current ruleset.

The server handles call metrics and transcripts. These records represent sensitive conversational data that must be managed carefully within your multi-agent debate structure.

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