How to Use the Umbraco MCP in AutoGen

Q: How do I determine available schemas using Umbraco and AutoGen?

The listdocumenttypes tool gives you all the defined content schemas. You pass this list to your agents, who then debate how best to categorize incoming data based on those types.

Q: Can AutoGen help me manage Umbraco drafts? With Umbraco and AutoGen?

Yes. By using getmanagementdocument, your agents can retrieve specific draft records for review. They then debate the necessary changes before suggesting an update via updatecmsdocument.

Q: If I want to create a new record, how does Umbraco and AutoGen help?

You use createcmsdocument with the tool. Your agents work together to construct the perfect JSON payload, ensuring all required fields are present before executing the final creation call.

Q: Is querying Umbraco content enough for AutoGen?

It's a starting point. You use querydeliverycontent to get data, but AutoGen excels when multiple agents challenge the interpretation of that data, leading to a final, consensus-based action.

Achieve consensus on Umbraco content decisions with AutoGen.

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Create your Vinkius account to connect Umbraco 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 Umbraco with AutoGen

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Perplexity

Negotiating Content Updates using MCP Server

Suppose a team needs to update an article, but the required changes are complex. You use `update_cms_document` and let your agents debate which fields need changing. One agent might argue for updating the SEO fields while another insists on revising the body copy. The consensus-driven process forces deliberation. The final decision is a single, agreed-upon JSON payload passed to the Umbraco API.

Risk Assessment for Deletion with AutoGen

Deleting content is risky. You use `delete_cms_document` only after your agents have debated whether it’s necessary. A 'Safety Agent' flags potential dependencies, while a 'Performance Agent' might argue that archiving instead is better. The system doesn't execute the delete until multiple perspectives agree on the action.

Comparing Content Options with AutoGen

You need to decide if content A or content B should be published. You run `list_delivery_content` and then use `query_delivery_content` multiple times, feeding the results to different agents for comparison. They challenge each other's interpretations of the data. The output isn't just a list; it’s a reasoned argument about which dataset is superior.

Setup guide

Set up Umbraco 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 Umbraco 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="Umbraco_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

The `list_document_types` tool gives you all the defined content schemas. You pass this list to your agents, who then debate how best to categorize incoming data based on those types.

Yes. By using `get_management_document`, your agents can retrieve specific draft records for review. They then debate the necessary changes before suggesting an update via `update_cms_document`.

The server handles document content (structured JSON), media assets, and comprehensive delivery records. Your agents treat these different formats as distinct pieces of evidence during their deliberation.

You use `create_cms_document` with the tool. Your agents work together to construct the perfect JSON payload, ensuring all required fields are present before executing the final creation call.

It's a starting point. You use `query_delivery_content` to get data, but AutoGen excels when multiple agents challenge the *interpretation* of that data, leading to a final, consensus-based action.

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