How to Use the Hiveage MCP in LlamaIndex

Q: Does Hiveage support semantic search in LlamaIndex?

Yes. Once you index the output of tools like listestimates, you can run semantic queries against your billing history to find quotes by description or client.

Q: Can Hiveage data be updated by my LlamaIndex agent?

You can use write-capable tools like recordpayment to update your account. The agent performs the action, and your index reflects the current state.

Q: What is the best way to filter Hiveage tools in LlamaIndex?

Use the allowedtools parameter to restrict the agent to read-only operations. This keeps your account data safe while allowing your agent to query the index.

Ground your LlamaIndex knowledge base in real-time billing data from your Hiveage account.

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Connect Hiveage MCP to LlamaIndex

Create your Vinkius account to connect Hiveage 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 Hiveage with LlamaIndex

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Index Hiveage invoices for RAG

Use `list_invoices` to pull your billing history into a vector store. LlamaIndex then makes these records searchable by your LLM for grounded, accurate answers. Stop guessing about past payments or outstanding balances. Your agent queries the index to retrieve precise data points from your actual account history.

Search customer profiles via LlamaIndex

Fetch contact info using `get_customer_details` and append it to your knowledge base. This keeps your agent updated on current client statuses and billing addresses. Everything becomes part of a unified index. Your agent finds the right details without hallucinating outdated or incorrect information.

Query tax profiles and billing items

Index your configured settings using `list_tax_profiles` and `list_billing_items`. This gives your agent a complete context of your business rules and service rates. Your RAG application references these items when generating new quotes or checking invoice accuracy. You get answers based on the live setup of your account.

Setup guide

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

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Common questions about Hiveage MCP in LlamaIndex

You initialize the client and convert the tools to a format compatible with your agent. This allows your index to pull live data directly from your account.

Yes. Once you index the output of tools like `list_estimates`, you can run semantic queries against your billing history to find quotes by description or client.

You can use write-capable tools like `record_payment` to update your account. The agent performs the action, and your index reflects the current state.

Use the allowed_tools parameter to restrict the agent to read-only operations. This keeps your account data safe while allowing your agent to query the index.

The server transmits data over encrypted channels to the sandbox. Your financial records are never indexed permanently; they exist only within the context of your specific query session.

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