Altoviz 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 Altoviz as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Altoviz. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Altoviz?"
)
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 Altoviz MCP Server
Connect your Altoviz account to your AI agent to unlock professional business management and automated invoicing. From creating and auditing sale invoices to monitoring real-time expenses and managing customer profiles, your agent handles your back-office operations through natural conversation.
LlamaIndex agents combine Altoviz 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
- Invoicing Orchestration — List, retrieve, and create professional sale invoices and quotes (devis)
- Accounting Management — Monitor business receipts (dépenses) and retrieve supplier details
- Customer Oversight — List and manage customer profiles, ensuring your business network is always updated
- Product Management — List products and retrieve inventory details to manage your catalog
- Financial Insights — Quickly identify overdue invoices or retrieve specific transaction details directly from your chat interface
The Altoviz 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 Altoviz to LlamaIndex via MCP
Follow these steps to integrate the Altoviz 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 Altoviz
Why Use LlamaIndex with the Altoviz MCP Server
LlamaIndex provides unique advantages when paired with Altoviz through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Altoviz tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Altoviz tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Altoviz, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Altoviz tools were called, what data was returned, and how it influenced the final answer
Altoviz + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Altoviz MCP Server delivers measurable value.
Hybrid search: combine Altoviz real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Altoviz 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 Altoviz for fresh data
Analytical workflows: chain Altoviz queries with LlamaIndex's data connectors to build multi-source analytical reports
Altoviz MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Altoviz to LlamaIndex via MCP:
get_customer_details
Get customer metadata
get_product_details
Get product metadata
get_sale_invoice_details
Get invoice metadata
get_sale_quote_details
Get quote metadata
list_customers
List customers
list_products
List catalog products
list_receipts
List business receipts/expenses
list_sale_invoices
List sale invoices
list_sale_quotes
List sale quotes
list_suppliers
List suppliers
Example Prompts for Altoviz in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Altoviz immediately.
"List the last 5 sale invoices in Altoviz."
"Show me details for customer 'John Doe'."
"List the products in my catalog."
Troubleshooting Altoviz MCP Server with LlamaIndex
Common issues when connecting Altoviz to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAltoviz + LlamaIndex FAQ
Common questions about integrating Altoviz 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 Altoviz 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 Altoviz to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.