How to Use the Gridscale (IaaS & PaaS Cloud Hosting API) MCP in AutoGen
Let AutoGen agents debate and coordinate cloud deployments, verifying server metrics and network states before making changes.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Gridscale (IaaS & PaaS Cloud Hosting API) MCP to AutoGen
Create your Vinkius account to connect Gridscale (IaaS & PaaS Cloud Hosting API) 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.
Multi-agent negotiation for server provisioning
`create_server` runs only after your AutoGen agents reach a consensus on resource needs and budget limits. A developer agent proposes a configuration, a finance agent checks the specs, and a security agent reviews the network layout before triggering the build. This collaborative check prevents accidental over-provisioning and ensures every new node matches your team's deployment policies. The agents resolve conflicts in their group chat before any actual API calls are executed.
Coordinate safe shutdowns via this MCP Server
`shutdown_server` is executed only after a performance agent and a safety agent agree it is safe to do so. The safety agent checks `get_server_power` and active traffic, while the performance agent confirms the node is redundant. This prevents accidental outages. Once they agree, the designated agent executes the ACPI shutdown. The agents then monitor the power state and log the successful completion of the maintenance task in their shared chat history.
Automated IP and storage routing debates
`link_ip_to_server` gets called after your agents determine the optimal routing path for a new instance. They query `list_ips` and `list_networks` to find an available address that matches the required security zone. For storage, they verify the machine's state using `get_server_power`. If the server is active, they coordinate the timing to execute `shutdown_server`, run `link_storage_to_server`, and then boot it back up using `set_server_power` without human intervention.
Set up Gridscale (IaaS & PaaS Cloud Hosting API) 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Gridscale (IaaS & PaaS Cloud Hosting API) tools and returns structured results.
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="Gridscale (IaaS & PaaS Cloud Hosting API)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Gridscale (IaaS & PaaS Cloud Hosting API) data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Gridscale (IaaS & PaaS Cloud Hosting API)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Gridscale (IaaS & PaaS Cloud Hosting API) data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Gridscale. 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 Gridscale (IaaS & PaaS Cloud Hosting API) MCP in AutoGen
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