How to Use the Builder MCP in AutoGen

Q: How do AutoGen agents coordinate Builder CMS updates?

One agent drafts the update payload using createvisualblock, and another agent verifies it against the schema. They debate any validation errors before pushing the final payload to your space.

Q: How do agents handle media validation in Builder with AutoGen?

An asset agent runs getmediafile to verify an image exists, then shares the metadata with the layout agent. The layout agent then updates the target block with the verified asset ID.

Let AutoGen agents debate and coordinate Builder CMS changes before pushing them live.

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Connect Builder MCP to AutoGen

Create your Vinkius account to connect Builder 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 Builder with AutoGen

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Multi-agent consensus for Builder updates

The `create_visual_block` tool creates new content entries or visual blocks inside a Builder model. Your copywriter agent uses this tool to draft new landing page sections, while your editor agent coordinates by calling `get_single_content` to inspect the live draft before agreeing on the final publish. This collaborative loop ensures that no agent pushes unverified changes to your CMS. They debate the layout structure and only execute the update once both agents sign off on the payload.

Schema validation via AutoGen MCP Server tools

The `get_model_schema` tool retrieves the exact field structure and schema definitions for a single model. One agent runs this tool to extract the field rules, while a second agent checks the draft content against those rules before writing data. If a validation error occurs, the agents discuss the failure and adjust the payload parameters. This prevents broken schemas from ever reaching your live Builder environment.

Automated cleanup debates

The `count_model_entities` tool quickly counts the number of live items stored within a specific model. A performance agent runs this tool to flag bloated models with too many old entries, then debates with a content agent to decide which items to remove using `wipe_visual_block`. The agents use `search_active_models` to find obsolete structures and coordinate the cleanup. You get a clean, optimized CMS space without manually auditing thousands of visual blocks.

Setup guide

Set up Builder 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 Builder 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="Builder_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Builder MCP in AutoGen

One agent drafts the update payload using `create_visual_block`, and another agent verifies it against the schema. They debate any validation errors before pushing the final payload to your space.

Yes, the server supports both stdio and Streamable HTTP transports. You register the tools with your AssistantAgent using the provided adapter.

An asset agent runs `get_media_file` to verify an image exists, then shares the metadata with the layout agent. The layout agent then updates the target block with the verified asset ID.

Use the mcp server tools adapter to convert the Vinkius HTTP endpoint into AutoGen-compatible MCP tools. Pass the resulting list to your AssistantAgent constructor.

The server processes your media metadata and visual blocks inside a secure, ephemeral V8 isolate. No data is stored or logged outside your active session, ensuring your content remains private.

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