Kentico (CMS & DXP) 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 Kentico (CMS & DXP) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Kentico (CMS & DXP). "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Kentico (CMS & DXP)?"
)
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 Kentico (CMS & DXP) MCP Server
Connect your Kentico Xperience project to any AI agent and take full control of your digital experience platform (DXP) and enterprise CMS through natural conversation.
LlamaIndex agents combine Kentico (CMS & DXP) tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through 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
- Document Orchestration — Retrieve and update site pages and documents based on alias paths, cultures, and site names directly from your agent
- System Object Management — Create, list, and mutate general system objects (roles, templates, settings) using structured REST mappings
- User CRM & Audit — List global platform users and retrieve detailed account profiles, including roles and metadata securely
- Custom Table Analytics — Extract tabular data from Kentico custom tables to monitor internal registries and business-specific data models
- Schema Visibility — Discover and inspect Kentico object types and scalar properties to understand your project's underlying data structure
- Content Lifecycle — Perform deep property mutations on existing documents or irreversibly delete unused system objects to maintain an optimized repository
The Kentico (CMS & DXP) 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 Kentico (CMS & DXP) to LlamaIndex via MCP
Follow these steps to integrate the Kentico (CMS & DXP) 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 Kentico (CMS & DXP)
Why Use LlamaIndex with the Kentico (CMS & DXP) MCP Server
LlamaIndex provides unique advantages when paired with Kentico (CMS & DXP) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kentico (CMS & DXP) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kentico (CMS & DXP) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kentico (CMS & DXP), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kentico (CMS & DXP) tools were called, what data was returned, and how it influenced the final answer
Kentico (CMS & DXP) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kentico (CMS & DXP) MCP Server delivers measurable value.
Hybrid search: combine Kentico (CMS & DXP) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kentico (CMS & DXP) 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 Kentico (CMS & DXP) for fresh data
Analytical workflows: chain Kentico (CMS & DXP) queries with LlamaIndex's data connectors to build multi-source analytical reports
Kentico (CMS & DXP) MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Kentico (CMS & DXP) to LlamaIndex via MCP:
create_system_object
Create a new Kentico system object
delete_system_object
Delete a Kentico system object
get_single_object
Get a specific Kentico system object by ID
get_site_document
Get a document from the Kentico Xperience CMS
get_user
Get details for a specific Kentico user
list_custom_table_rows
List rows from a Kentico custom table
list_system_objects
g., roles provisions, page templates) from Kentico REST. List Kentico system objects by type
list_users
user in Kentico. List global Kentico users
update_site_document
Update an existing document in the Kentico CMS
update_system_object
Update an existing Kentico system object
Example Prompts for Kentico (CMS & DXP) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kentico (CMS & DXP) immediately.
"Get the 'Home' page document from site 'CorporateSite' in 'en-us' culture"
"Update the DocumentName of '/About-Us' to 'Our Team' on currentsite"
"List all rows from the custom table 'MyCompany.Inventory'"
Troubleshooting Kentico (CMS & DXP) MCP Server with LlamaIndex
Common issues when connecting Kentico (CMS & DXP) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKentico (CMS & DXP) + LlamaIndex FAQ
Common questions about integrating Kentico (CMS & DXP) 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 Kentico (CMS & DXP) 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 Kentico (CMS & DXP) to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.