How to Use the Altoviz MCP in LlamaIndex

Q: How do I configure the Altoviz MCP server in LlamaIndex?

Install llama-index-tools-mcp via pip. Create a BasicMCPClient with your Vinkius URL, then wrap it in an McpToolSpec.

Q: Can LlamaIndex filter which Altoviz tools are available?

You pass an allowedtools list to the tool spec. This restricts the agent to specific operations like listcustomers while blocking invoice access.

Q: Does Altoviz sync my entire database into LlamaIndex?

No. The agent fetches records on demand using tools like getsalequotedetails. It only indexes the data required to answer the immediate user query.

Index your Altoviz invoices and customer records directly into LlamaIndex vector stores.

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Connect Altoviz MCP to LlamaIndex

Create your Vinkius account to connect Altoviz 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 Altoviz with LlamaIndex

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Feed LlamaIndex live catalog data

Executing `list_products` pulls your current catalog into the LlamaIndex pipeline. RAG applications fall apart when product pricing changes. The framework converts these JSON records into searchable document nodes. Your semantic search now queries actual inventory instead of stale PDFs. When a user asks about a specific item, the engine retrieves the exact `get_product_details` output. Hallucinations drop to zero because the context window relies on live API data.

Query invoices via MCP Server

Running `list_sale_invoices` extracts your billing records for immediate indexing. Financial history usually lives in isolated silos. You pair this tool with `get_sale_invoice_details` to build a complete, queryable knowledge base of past transactions. Users ask plain English questions about their revenue. The `FunctionAgent` fetches the missing data chunks via the MCP Server, embeds them, and returns a grounded answer. Complex financial reporting becomes a simple search operation.

Embed supplier and receipt context

The `list_receipts` and `list_suppliers` MCP tools provide the raw materials for expense reconciliation. Auditing expenses requires matching receipts to vendor profiles. LlamaIndex ingests both datasets to map spending patterns. Analysts query the resulting index to find anomalies. If a receipt looks suspicious, the system cross-references the supplier metadata. You get answers backed by hard database entries.

Setup guide

Set up Altoviz 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 Altoviz 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 Altoviz tools.",
)
response = await agent.run("List recent Altoviz 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 Altoviz. 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 Altoviz MCP in LlamaIndex

Install `llama-index-tools-mcp` via pip. Create a `BasicMCPClient` with your Vinkius URL, then wrap it in an `McpToolSpec`.

You pass an `allowed_tools` list to the tool spec. This restricts the agent to specific operations like `list_customers` while blocking invoice access.

No. The agent fetches records on demand using tools like `get_sale_quote_details`. It only indexes the data required to answer the immediate user query.

MCP provides a standardized interface that LlamaIndex understands natively. You skip writing custom schema parsers for every endpoint.

Vinkius routes traffic through a zero-trust architecture. Expense amounts and vendor names from `list_receipts` never touch disk. Your endpoint token is the only authentication required, keeping credentials out of your codebase.

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