Can my AI agent create new pages from specific templates?

Yes. Ask the agent to list your content templates to find the ID of the template you want (e.g., 'Article' or 'Landing Page'). Then, provide the parent path where you want the new items to exist. Your agent will call the Sitecore API to instantly generate the new items based on those schemas without requiring you to open the Content Editor.

How can I bulk update metadata for outdated pages?

First, ask your agent to search for the specific path or keyword to get all related page IDs. Then, command the agent to update each item by passing a JSON with the new fields (like updating SEO descriptions or valid dates). The AI parses your instruction and dynamically executes the updates directly into Sitecore.

Is it possible to check whether an item is published or still in Draft mode?

Absolutely. You can request the agent to get the workflow state of any given item path. The agent will respond with the current state (e.g., Draft, Awaiting Approval, or Published), making it easy to track content pipelines.

Sitecore MCP Server for Pydantic AI 9 tools — connect in under 2 minutes

Name: Sitecore
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 9 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Sitecore through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

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

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Sitecore "
            "(9 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Sitecore?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Sitecore MCP Server

Connect your Sitecore instance to any AI agent and take full control of your enterprise CMS through natural conversation. Execute headless content operations without navigating the complex Sitecore Content Editor.

Pydantic AI validates every Sitecore tool response against typed schemas, catching data inconsistencies at build time. Connect 9 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Item Management — Retrieve, create, update, and delete Sitecore items using their path or unique ID
Content Search — Search deeply across your content tree using keywords, templates, and dates
Site navigation — List item children to traverse the content tree hierarchy natively
Templates & Layouts — List available templates and retrieve presentation/layout details (renderings and placeholders) for specific pages
Workflows — Check the current workflow state of any item (e.g., Draft, Review, Published)

The Sitecore MCP Server exposes 9 tools through the Vinkius. Connect it to Pydantic AI 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 Sitecore to Pydantic AI via MCP

Follow these steps to integrate the Sitecore MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 9 tools from Sitecore with type-safe schemas

Why Use Pydantic AI with the Sitecore MCP Server

Pydantic AI provides unique advantages when paired with Sitecore through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Sitecore integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Sitecore connection logic from agent behavior for testable, maintainable code

Sitecore + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Sitecore MCP Server delivers measurable value.

Type-safe data pipelines: query Sitecore with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Sitecore tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Sitecore and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Sitecore responses and write comprehensive agent tests

Sitecore MCP Tools for Pydantic AI (9)

These 9 tools become available when you connect Sitecore to Pydantic AI via MCP:

create_content_item

Requires parent ID, item name, and template ID. Creates a new item in the Sitecore content tree

delete_content_item

This action is irreversible. Permanently deletes a Sitecore item

get_item_details

Retrieves details for a specific Sitecore item

get_item_layout

Retrieves the layout or presentation details for an item

get_workflow_state

Retrieves the current workflow state of an item

list_content_templates

g., "Page", "Article") are available for creating new items. Lists available content templates

list_item_children

Lists the immediate children of a specific item

search_content

Useful for broad discovery across the CMS. Searches for content items in Sitecore

update_content_item

Provide a JSON string of field name/value pairs. Updates the fields of an existing Sitecore item

Example Prompts for Sitecore in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Sitecore immediately.

"Can you check the workflow state for the `/sitecore/content/Home/AboutUs` item?"

"List the immediate children under `/sitecore/content/Home/Products`."

"Create a new item named 'SpringCampaign' using template `5F22...` under parent ID `3D66...`."

Troubleshooting Sitecore MCP Server with Pydantic AI

Common issues when connecting Sitecore to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Sitecore + Pydantic AI FAQ

Common questions about integrating Sitecore MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Sitecore MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.