How to Use the CAMB.AI MCP in AutoGen

Let your AutoGen agents debate and execute CAMB.AI audio tasks for complex media projects.

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Connect CAMB.AI MCP to AutoGen

Create your Vinkius account to connect CAMB.AI 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 CAMB.AI with AutoGen

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Debate audio tasks in AutoGen

Assign `create_dubbing` to a specialized agent that proposes translation strategies. Other agents in your group chat can challenge these choices, ensuring you reach a consensus on the correct target language. This setup prevents errors by forcing agents to argue over the `list_target_languages` results. They verify the requirements before any actual dubbing job starts, leading to more accurate project outcomes.

Manage voice clones with AutoGen

Have your agents negotiate the creation of new voice profiles. One agent might suggest `create_voice_clone` based on a specific audio sample, while another monitors the status via `get_job_status` to ensure success. This multi-agent approach handles the back-and-forth of audio processing. The agents keep the conversation focused on the result, ensuring that every voice clone meets the quality standards defined by the user.

Use this MCP Server for consensus

Integrate the server into your agent group to handle all audio communication. The agents use `list_voices` to agree on a voice before initiating a task, making the entire process transparent and collaborative. By including the server as a tool resource, you allow your agents to pull real-time data from the API. They decide together which job to prioritize based on the current system state, effectively managing your workload.

Setup guide

Set up CAMB.AI 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 CAMB.AI 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="CAMB.AI_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Use the MCP tool adapter to convert the server tools into a format AutoGen understands. Then, add these tools to your AssistantAgent to enable voice and dubbing operations.

It allows for multi-agent deliberation. You can have one agent propose a translation and another check the status, ensuring a higher level of oversight for your media projects.

The server operates within an ephemeral sandbox, meaning your custom voice data is only processed during the active agent conversation. We do not persist your sensitive audio assets beyond the required task duration.

Absolutely. Agents can call the language listing tools, discuss the options, and then decide on the best target language for the final dubbing task.

Define the agent's system prompt to explicitly reference the available audio tools. This guides the agents to call the correct function when they need to perform a specific action.

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