How to Use the ElevenLabs MCP in AutoGen

Enable multi-agent debate in AutoGen using ElevenLabs to negotiate voice styles and production costs.

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Connect ElevenLabs MCP to AutoGen

Create your Vinkius account to connect ElevenLabs 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 ElevenLabs with AutoGen

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Debate voice styles in AutoGen

Assign agents to `list_voices` and `list_models` to discuss which audio profile fits the user's request. One agent can argue for high-quality models while another focuses on latency. They reach a consensus before hitting the `text_to_speech` endpoint. This debate prevents costly mistakes and ensures the final audio matches your brand requirements.

Manage ElevenLabs budgets in AutoGen

Let a finance-focused agent call `get_subscription` to monitor character counts. If the limit is near, the agent can force the system to switch to a cheaper model or pause production. It creates a self-regulating system. You don't have to watch the dashboard because your agents are actively negotiating the budget in real-time.

Coordinate projects with ElevenLabs and AutoGen

Use `list_projects` to allow your agents to track ongoing dubbing tasks. Agents can check the status of multiple projects and delegate the next step to the appropriate worker. It turns your audio workflow into a collaborative effort. The agents update each other on project completion, keeping your entire pipeline moving without manual intervention.

Setup guide

Set up ElevenLabs 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 ElevenLabs 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="ElevenLabs_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You provide the tool list to the AssistantAgent constructor. The agents then negotiate which one is best suited to call `text_to_speech` for the current task.

Yes. You can set up a debate where one agent proposes a voice using `get_voice` and another rejects it based on criteria like tone or cost.

The McpToolAdapter automatically converts the ElevenLabs schema into a format your AutoGen agents can understand. They call the functions just like any other tool.

No. The MCP server handles the authentication securely. The agents only interact with the tool interface provided by the server.

The server restricts access to sensitive user profile info. Only the agents you explicitly authorize can call `get_user_info` or other sensitive tools.

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