How to Use the Imagine.io MCP in AutoGen

Q: How do I register the Imagine.io MCP Server tools in AutoGen?

Install the extension with pip install -U "autogen-extmcp". Use mcpservertools with your Vinkius HTTP endpoint to retrieve the tools, then pass that list directly to your AssistantAgent constructor.

Q: How do AutoGen agents collaborate on an Imagine.io render job?

One agent can query scene details using getscene, a second agent selects the materials via listmaterials, and a third agent executes the createrenderjob call once both parameters are approved.

Q: Can AutoGen handle API connection drops during an Imagine.io render?

Yes. Your monitoring agent can call checkimaginestatus to verify connectivity. If the API is offline, the agent can pause the conversation and retry the getjobstatus call once the connection is restored.

Run multi-agent debates in AutoGen to validate and execute Imagine.io 3D render workflows.

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Connect Imagine.io MCP to AutoGen

Create your Vinkius account to connect Imagine.io 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 Imagine.io with AutoGen

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Coordinate multi-agent rendering pipelines

The `create_render_job` tool allows your AutoGen agents to initiate high-fidelity renders after agreeing on the scene parameters. One agent can draft the layout while a critic agent checks the configuration before triggering the job. Once the task starts, a dedicated monitoring agent uses `get_job_status` to poll for completion. This consensus-driven approach ensures you only spend render credits when all design constraints are fully satisfied.

Resolve material conflicts through agent debate

The `list_materials` tool provides a complete list of textures and finishes available in your account. Your agents can debate which material suits a specific product based on catalog guidelines. After resolving the debate, the selected material ID is passed to the render tool. This collaborative loop guarantees that your automated renders match your brand standards without manual oversight.

Audit accounts and credit usage via this MCP Server

The `get_account` tool retrieves your current credit balance and profile details directly from the API. This MCP Server gives your budget-tracking agent the exact data it needs to approve or pause heavy rendering tasks. By checking the balance before running `create_render_job`, your agents prevent unexpected overages. They can also use `check_imagine_status` to verify API availability before launching a massive batch job.

Setup guide

Set up Imagine.io 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 Imagine.io 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="Imagine.io_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Imagine.io 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="Imagine.io_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Install the extension with `pip install -U "autogen-ext[mcp]"`. Use `mcp_server_tools` with your Vinkius HTTP endpoint to retrieve the tools, then pass that list directly to your `AssistantAgent` constructor.

One agent can query scene details using `get_scene`, a second agent selects the materials via `list_materials`, and a third agent executes the `create_render_job` call once both parameters are approved.

Yes. Your monitoring agent can call `check_imagine_status` to verify connectivity. If the API is offline, the agent can pause the conversation and retry the `get_job_status` call once the connection is restored.

Yes, the adapter handles schema conversion automatically for both transport methods, allowing your agents to communicate with the Vinkius hosted server over secure HTTP streams.

The Vinkius runtime executes all tool calls in a secure, isolated sandbox. Your raw scene geometries and account details remain private, as the server only exposes the specific metadata required to execute your active tasks.

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