Can it easily retrieve the content of a page assuming I only know its URL path?

Absolutely. Instruct the agent to 'get_delivery_content_by_path' and supply something like '/home/about'. It traverses the Delivery API native routing map and returns perfectly all inner block grids and content variables attached.

How do I ensure the JSON payloads for `create_cms_document` are exactly what Umbraco expects?

Use the agent to first run 'list_document_types'. It pulls down the global schema blueprints. The LLM can explicitly read the allowed field types (like rich text or media pickers) and logically construct the insertion matching it exactly.

Does it pull media details dynamically?

Yes. Pinging 'list_media_assets' grants full insight over all stored visuals inside your Umbraco media containers, returning URL addresses alongside fundamental dimension formats so the agent can reference them anywhere.

Umbraco MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Umbraco
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Umbraco through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Umbraco Assistant",
            instructions=(
                "You help users interact with Umbraco. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Umbraco"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Umbraco MCP Server

Connect your Umbraco CMS backend to any AI agent and take full autonomous control bridging the powerful Delivery and Management APIs purely through natural conversation.

The OpenAI Agents SDK auto-discovers all 10 tools from Umbraco through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Umbraco, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Delivery API Traversing — Instantly list public pages, query by content type, or securely fetch structured fields by their exact domain paths organically
Backoffice Document Control — Push new document permutations natively adhering to your configured schemas without opening a single GUI panel
Site Mutations — Command the targeted removal of any outdated published nodes or force updates to internal fields seamlessly via update_cms_document
Schema & Media Insight — Grab absolute lists tracking your stored binary media files alongside the global Document Types blueprints mapped out natively

The Umbraco MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Umbraco to OpenAI Agents SDK via MCP

Follow these steps to integrate the Umbraco MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Umbraco

Why Use OpenAI Agents SDK with the Umbraco MCP Server

OpenAI Agents SDK provides unique advantages when paired with Umbraco through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Umbraco + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Umbraco MCP Server delivers measurable value.

Automated workflows: build agents that query Umbraco, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Umbraco, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Umbraco tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Umbraco to resolve tickets, look up records, and update statuses without human intervention

Umbraco MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Umbraco to OpenAI Agents SDK via MCP:

create_cms_document

Provide the document data as a JSON object adhering to the schema. Creates a new document in the Umbraco CMS

delete_cms_document

This action is irreversible. Permanently deletes a document from the Umbraco CMS

get_delivery_content_by_id

Retrieves a specific content item by its GUID or numeric ID via Delivery API

get_delivery_content_by_path

g., "/home/about"). Retrieves a specific content item by its URL path

get_management_document

Retrieves a specific document via the Umbraco Management API (Drafts/Backoffice)

list_delivery_content

Supports pagination via take and skip. Lists content available via the Umbraco Delivery API

list_document_types

Lists all document types (schemas) defined in Umbraco

list_media_assets

Lists media assets (images, files) from the Umbraco Media library

query_delivery_content

g., "contentType:blogPost"). Filters content items using the Umbraco Delivery API query syntax

update_cms_document

Provide the document ID and JSON updates. Updates fields of an existing document in Umbraco

Example Prompts for Umbraco in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Umbraco immediately.

"Use the delivery API to get the content from '/products/new-feature' and list out its properties."

"Look up our Document Types to see the exact schema required for a 'BlogPost'. Then create one JSON draft placeholder payload based on it."

"Delete the backoffice document holding ID d6ef43..."

Troubleshooting Umbraco MCP Server with OpenAI Agents SDK

Common issues when connecting Umbraco to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Umbraco + OpenAI Agents SDK FAQ

Common questions about integrating Umbraco MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.