How to Use the Anyscale MCP in AutoGen

Enable multi-agent debate and consensus on your Anyscale infrastructure using AutoGen.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Anyscale MCP to AutoGen

Create your Vinkius account to connect Anyscale 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.

GDPR Free for Subscribers

Setup Anyscale with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate Anyscale ops in AutoGen

Set up one agent to monitor `list_jobs` while another evaluates resource usage. They debate the necessity of stopping or starting tasks based on the data. This mimics how a human team reaches a decision. You get a consensus-driven approach to infrastructure management rather than blind execution.

Secure Anyscale agents with AutoGen

Assign a security-focused agent to check `list_services` for unauthorized deployments. It challenges the primary agent if it detects a configuration that violates your rules. This adds a layer of negotiation to your pipeline. Agents push back on instructions that don't meet your pre-defined safety standards.

Streamline decision making in AutoGen

Use `chat_completion` to let agents discuss the best model for a specific workload. They converge on the most efficient choice after reviewing the current environment. This removes the burden of manual oversight. Your agents handle the deliberation and confirm their choice before executing the final command.

Setup guide

Set up Anyscale 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 Anyscale 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="Anyscale_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Anyscale_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install the MCP extension for AutoGen and pass the server tools to your AssistantAgent. The adapter handles the schema mapping so agents understand the API.

Yes, you can set up multiple agents with conflicting goals to debate the queue. They use the tool output to reach a consensus on what to run next.

Vinkius provides a zero-trust sandbox environment. Your data is restricted to the ephemeral session and protected by our managed authentication.

The server supports HTTP streamable transports. This allows your agents to participate in long-running debates without blocking the main event loop.

We enforce strict access controls on every tool call. Only the specific job metadata required for the agent's current deliberation is exposed during the conversation.

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