How to Use the CoreWeave (AI GPU Cloud) MCP in AutoGen

Q: Can I limit which AutoGen agents have permission to modify CoreWeave (AI GPU Cloud) VPCs?

Yes, you can register tools selectively. Give createvpc only to your network specialist agent, while leaving other agents with read-only tools like listvpcs.

Q: How do AutoGen agents handle long-running CoreWeave (AI GPU Cloud) provisioning tasks?

The agent executes createcluster and then yields control. A monitoring agent polls getcluster in a loop, updating the conversation when the status changes to active.

Let specialized AutoGen agents debate and coordinate CoreWeave GPU provisioning and network isolation.

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Connect CoreWeave (AI GPU Cloud) MCP to AutoGen

Create your Vinkius account to connect CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) with AutoGen

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Consensus-driven GPU cluster provisioning via AutoGen

The CoreWeave MCP Server enables multi-agent negotiation over hardware allocation using `create_capacity_claim` and `list_capacity_claims`. A budget agent and a performance agent can debate the cost-benefit of reserving H100s versus A100s. Once they agree on a configuration, the executor agent runs `create_cluster` to build the Kubernetes environment. This ensures your infrastructure setup matches both technical requirements and financial constraints.

Automated incident response via coordinated agents

You can set up a multi-agent loop where one agent monitors system health using `query_metrics`. If anomalies are detected, it alerts a debugging agent to inspect the logs via `query_logs`. If the debugging agent determines a deployment is corrupted, it requests the executor agent to run `update_deployment`. The entire recovery process happens autonomously through structured agent debate.

Collaborative network and gateway management

This MCP Server allows your AutoGen security agent to review network setups using `list_vpcs` and `list_gateways`. If it detects an open routing path, it challenges the deployment agent's configuration. The deployment agent must then execute `update_gateway` or `update_vpc` to restrict access. This collaborative loop guarantees that public endpoints are never exposed by mistake.

Setup guide

Set up CoreWeave (AI GPU Cloud) 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 CoreWeave (AI GPU Cloud) 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="CoreWeave (AI GPU Cloud)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent CoreWeave (AI GPU Cloud) 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="CoreWeave (AI GPU Cloud)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent CoreWeave (AI GPU Cloud) 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 CoreWeave. 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 CoreWeave (AI GPU Cloud) MCP in AutoGen

You define a group chat manager that requires consensus before executing destructive tools like `delete_cluster`. The agents must present metrics and log data to justify the teardown.

Yes, you can register tools selectively. Give `create_vpc` only to your network specialist agent, while leaving other agents with read-only tools like `list_vpcs`.

The agent executes `create_cluster` and then yields control. A monitoring agent polls `get_cluster` in a loop, updating the conversation when the status changes to active.

AutoGen uses the Streamable HTTP transport provided by Vinkius. This ensures fast, low-latency communication for every tool call.

Only your local AutoGen instance can access this information. Vinkius secures your API keys within a hardware-isolated V8 sandbox running the MCP Server, executing `list_capacity_claims` and `list_deployments` on demand without persisting any payload data.

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