How to Use the Umbraco MCP in Pydantic AI

Q: How does Pydantic AI handle complex Umbraco content changes?

When you run updatecmsdocument, the toolset validates both the input parameters and the returned data against your defined models. This guarantees that any change made to Umbraco is structurally sound.

Q: Can I check the available schemas in Umbraco using Pydantic AI?

Yes, calling listdocumenttypes exposes all defined content schemas. Since Pydantic validates everything, you get a reliable list of what types exist in Umbraco.

Q: If I retrieve content from Umbraco using Pydantic AI, is the data clean?

Absolutely. Every piece of data returned by tools like getdeliverycontentbypath is validated against a model at runtime. You'll get Python objects you can trust.

Q: What if I delete content from Umbraco using Pydantic AI?

The agent executes deletecmsdocument when instructed. Because the action is irreversible, the tool’s documentation emphasizes that this must be done intentionally and carefully.

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Connect Umbraco MCP to Pydantic AI

Create your Vinkius account to connect Umbraco to Pydantic AI 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 Pydantic AI

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Control Content Creation

Pydantic AI makes content creation safe. The agent uses `create_cms_document` to write new records, but every piece of data is validated against a Pydantic schema first. If the Umbraco API returns unexpected JSON, your agent fails LOUDLY. This level of type-safety means you never risk silent corruption when pushing content.

Precise Content Retrieval

You can retrieve specific articles using `get_delivery_content_by_path` or by ID with `get_delivery_content_by_id`. The resulting data is immediately validated, giving your agent clean, predictable Python objects. For bulk operations, `list_document_types` gives you the schema list, and `query_delivery_content` filters content items.

Full Umbraco Lifecycle Management

The MCP Server allows your agent to manage assets via `list_media_assets` and modify existing pages using `update_cms_document`. Everything is wrapped in type checks, from the schema list provided by `list_document_types` to the final asset updates. It’s a robust way to ensure every action taken on Umbraco adheres strictly to your defined data rules.

Setup guide

Set up Umbraco MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "umbraco-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Umbraco tools.",
)

result = await agent.run("List recent Umbraco transactions")
print(result.output)

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Common questions about Umbraco MCP in Pydantic AI

When you run `update_cms_document`, the toolset validates both the input parameters and the returned data against your defined models. This guarantees that any change made to Umbraco is structurally sound.

It handles structured text data, file references from media libraries, and document metadata (GUIDs, paths). The Pydantic validation ensures these data types are always correct for your agent.

Yes, calling `list_document_types` exposes all defined content schemas. Since Pydantic validates everything, you get a reliable list of what types exist in Umbraco.

Absolutely. Every piece of data returned by tools like `get_delivery_content_by_path` is validated against a model at runtime. You'll get Python objects you can trust.

The agent executes `delete_cms_document` when instructed. Because the action is irreversible, the tool’s documentation emphasizes that this must be done intentionally and carefully.

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