How to Use the Conductor (Netflix OSS) MCP in AutoGen

Q: What is the setup process for this MCP Server in AutoGen?

Install the extension with pip install -U "autogen-extmcp". Use mcpservertools with your Vinkius HTTP URL, then pass those tools directly to your AssistantAgent.

Run multi-agent debates in AutoGen to manage, validate, and recover Netflix Conductor workflows.

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Connect Conductor (Netflix OSS) MCP to AutoGen

Create your Vinkius account to connect Conductor (Netflix OSS) 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 Conductor (Netflix OSS) with AutoGen

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Manage Conductor runs via AutoGen multi-agent debate

Your AutoGen agents gain the power to coordinate execution paths using `execute_workflow` and `terminate_workflow`. A coordinator agent proposes a workflow execution, while a budget agent reviews the potential costs before confirming. This AutoGen consensus mechanism prevents runaway Conductor execution loops in production. The agents debate the necessity of the run before any API call is made.

Resolve Conductor failures using AutoGen agent consensus

By exposing `bulk_retry` and `bulk_resume` to your AutoGen agent group, this server automates recovery when jobs fail. A diagnostic agent analyzes the task logs, while a recovery agent proposes the correct retry parameters. They negotiate the best path forward to fix the Conductor system without breaking task dependencies. Only when both agents agree does the system trigger the bulk recovery tool.

Validate Conductor definitions with AutoGen agents

Your AutoGen agents can collaborate on schema changes using `validate_workflow_definition` and `update_workflow_definition`. A developer agent drafts the new workflow structure, and a security agent reviews it for compliance. They run interactive validation checks to catch Conductor errors before deployment. This collaborative AutoGen loop ensures only clean, secure Conductor definitions get deployed.

Setup guide

Set up Conductor (Netflix OSS) 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 Conductor (Netflix OSS) 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="Conductor (Netflix OSS)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Conductor (Netflix OSS) 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="Conductor (Netflix OSS)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Conductor (Netflix OSS) 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 Conductor (Netflix OSS). 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 Conductor (Netflix OSS) MCP in AutoGen

You register the tools with an AssistantAgent. The agents discuss the task in a group chat, and only the designated execution agent triggers tools like execute_workflow once consensus is reached.

Yes, your agent group can compile a list of target workflows and execute bulk_pause collectively. The debate loop ensures you only pause workflows that meet specific failure criteria.

Vinkius manages the authentication layer. Your AutoGen agents connect using a single endpoint token, so you don't need to manage individual keys inside your code.

Install the extension with pip install -U "autogen-ext[mcp]". Use mcp_server_tools with your Vinkius HTTP URL, then pass those tools directly to your AssistantAgent.

No, Vinkius runs every server instance in an isolated, ephemeral V8 sandbox. Your workflow execution payloads and queue sizes are protected by zero-trust isolation, ensuring no other tenant can ever access your Conductor data.

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