How to Use the Belong Australia MCP in LlamaIndex

Index your Belong Australia service history into LlamaIndex for searchable knowledge.

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Connect Belong Australia MCP to LlamaIndex

Create your Vinkius account to connect Belong Australia 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.

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Setup Belong Australia with LlamaIndex

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Index Belong Australia usage in LlamaIndex

Turn your ISP data into a searchable index. When you run `get_usage_data`, the output is embedded into your vector store for long-term recall. Your RAG pipeline now understands your broadband history. You can ask questions about past trends without hitting the live API every single time.

Ground LlamaIndex answers with Belong Australia

Stop guessing about your bills. Use `list_invoices` to populate your knowledge base with factual payment history. Your agent answers queries by referencing these indexed invoices. It avoids hallucinations by sticking to the data returned by the server.

Filter Belong Australia tools with LlamaIndex

Control which tools your agent touches. You can restrict the tool list to read-only functions like `get_user_profile` to prevent unauthorized changes. This granular access keeps your agent focused. It only indexes the information that matters for your specific RAG application.

Setup guide

Set up Belong Australia 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 Belong Australia 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 Belong Australia tools.",
)
response = await agent.run("List recent Belong Australia data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Belong Australia. 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.

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Common questions about Belong Australia MCP in LlamaIndex

Load the tools into the FunctionAgent. Once indexed, you can ask natural language questions about your account, and the agent will call the right tool to find the answer.

Yes, once you index the tool output, it stays in your vector store. This allows your agent to perform historical analysis on your service data.

It can. By listing invoices and indexing the text, the agent can provide a summary of your spending patterns over the last six months.

All traffic is routed through secure channels. Your LlamaIndex setup communicates over HTTPS to the Vinkius gateway.

We enforce strict ephemeral session policies. The server processes your billing PDFs and invoice line items in a memory-safe sandbox that clears immediately after the task finishes.

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