Umbraco MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Umbraco as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Umbraco. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Umbraco?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Umbraco tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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- Site Mutations — Command the targeted removal of any outdated published nodes or force updates to internal fields seamlessly via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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Umbraco MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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 10 tools from Umbraco
Why Use LlamaIndex with the Umbraco MCP Server
LlamaIndex provides unique advantages when paired with Umbraco through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Umbraco tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Umbraco tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Umbraco, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Umbraco tools were called, what data was returned, and how it influenced the final answer
Umbraco + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Umbraco MCP Server delivers measurable value.
Hybrid search: combine Umbraco real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Umbraco to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Umbraco for fresh data
Analytical workflows: chain Umbraco queries with LlamaIndex's data connectors to build multi-source analytical reports
Umbraco MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Umbraco to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Umbraco to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpUmbraco + LlamaIndex FAQ
Common questions about integrating Umbraco MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Umbraco with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Umbraco to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.