How to Use the Zentitle2 MCP in LlamaIndex

Q: Is this MCP Server suitable for complex RAG applications with LlamaIndex?

It's perfect. You combine live API calls (like getcustomerdetails) with document retrieval, creating a unified index that handles both structured data and unstructured text.

Index Zentitle2 license data into your knowledge base using LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Zentitle2 MCP to LlamaIndex

Create your Vinkius account to connect Zentitle2 to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Zentitle2 with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Indexing Customer Data with MCP Server

The `get_customer_details` tool retrieves specific customer records. When connected via LlamaIndex, this output doesn't just appear in a chat—it gets indexed into your vector store. You can then query past sessions and get answers grounded directly in that API data. Similarly, calling `list_customers` populates the index with multiple customer entries. This makes the historical record of client details available for semantic search across your entire knowledge base.

Tracking Entitlements via LlamaIndex

Building RAG applications requires accurate, live data. Use `get_entitlement_details` to fetch a specific entitlement's status and metadata. This output becomes part of your searchable knowledge base, letting you query not just documents, but actual license records. Need to find out what licenses are available? Calling `list_entitlements` populates the index with multiple licensing types, allowing LlamaIndex to answer complex questions about your product offerings.

Managing Codes and Products through LlamaIndex

Need to audit codes? The tools let you list all activation codes (`list_activation_codes`) and check details for a specific one using `get_activation_code_details`. This information gets indexed, meaning your agent can answer questions like, 'What was the status of code X last month?' For product context, running `list_products` feeds all licensed products into the index. You combine this with customer data to build a comprehensive understanding of what's covered.

Setup guide

Set up Zentitle2 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Zentitle2 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Zentitle2 tools.",
)
response = await agent.run("List recent Zentitle2 data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zentitle2. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Zentitle2 now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Zentitle2 MCP in LlamaIndex

LlamaIndex treats MCP tool output as source material. Instead of just calling the tools, it indexes the results into a vector store, allowing your agent to perform semantic search against live API data.

You're indexing structured licensing metadata: customer records, entitlement details, product SKUs, activation code information, and comprehensive lists of all those things.

Yes. Because the MCP tool output is indexed, you can query configurations or historical API results—like old customer details—and get answers grounded in the actual data.

It's perfect. You combine live API calls (like `get_customer_details`) with document retrieval, creating a unified index that handles both structured data and unstructured text.

The server touches specific licensing metadata: customer names, entitlement IDs, product SKUs, activation codes. By indexing this, you maintain a searchable record while keeping the raw source secure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript