How to Use the Conductor (Netflix OSS) MCP in Pydantic AI

Q: How do I connect the Conductor (Netflix OSS) MCP Server to my Pydantic AI agent?

Initialize an MCPToolset with your Vinkius HTTP endpoint. Pass this toolset into the toolsets parameter when creating your Pydantic AI Agent.

Execute type-safe executions inside Pydantic AI with runtime validation on every MCP workflow task.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Conductor (Netflix OSS) MCP to Pydantic AI

Create your Vinkius account to connect Conductor (Netflix OSS) to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Conductor (Netflix OSS) with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe execution via this MCP Server

This MCP server brings structural validation to your workflow engine. When your agent calls `get_workflow` or `get_task_definition`, the returned data is validated against strict Pydantic schemas at runtime. If the workflow engine returns unexpected fields, your agent fails loudly before executing bad logic. This prevents corrupted task definitions from breaking downstream production services.

Safe definition management

This schema registration server manages task and workflow definitions safely. The agent uses `create_task_definitions` and `create_workflow_definition` to register new tasks, validating the schemas before they hit the server. Modifying existing setups uses `update_task_definition` or `delete_task_definition`. The agent checks the current state using `get_task_definitions` to ensure no active runs depend on the deleted steps.

Robust run control

This execution control server manages active job states. The agent uses `pause_workflow`, `resume_workflow`, and `terminate_workflow` to manage execution states based on real-time application events. If a job fails, the agent calls `retry_workflow` or `restart_workflow` to recover. It can also use `rerun_workflow` to resume execution from a specific task ID with updated inputs.

Setup guide

Set up Conductor (Netflix OSS) MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "conductor-netflix-oss-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Conductor (Netflix OSS) tools.",
)

result = await agent.run("List recent Conductor (Netflix OSS) transactions")
print(result.output)

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Conductor (Netflix OSS) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Conductor (Netflix OSS) MCP in Pydantic AI

Initialize an `MCPToolset` with your Vinkius HTTP endpoint. Pass this toolset into the `toolsets` parameter when creating your Pydantic AI `Agent`.

Yes, it does. You can use this setup with OpenAI, Anthropic, Gemini, or local models since the validation layer runs entirely within your Python application.

The validation layer catches the schema mismatch instantly and throws an error. This prevents your agent from making decisions based on corrupted or hallucinated task data.

No, you don't. Vinkius hosts and manages the server lifecycle, exposing a single secure endpoint that your toolset connects to over HTTP or SSE.

Your workflow schemas and active definitions are transmitted over TLS directly to your execution cluster. The Vinkius sandbox operates in memory only, ensuring zero storage of your proprietary logic.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript