How do I find my Altoviz API Key?

Log in to your Altoviz account, navigate to your account settings or developer section, and generate a new API key. This key will be used as the `X-API-KEY` header.

Can I retrieve supplier invoices (receipts)?

Yes! Use the `list_receipts` tool to get a list of expenses/receipts recorded in Altoviz.

Are sale quotes supported?

Yes, you can use the `list_sale_quotes` tool to see existing quotes, and `get_sale_quote_details` for specific information.

Altoviz MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Altoviz
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Altoviz through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Altoviz "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Altoviz?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

Pydantic AI validates every Altoviz tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

Follow these steps to integrate the Altoviz MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 with type-safe schemas

Why Use Pydantic AI with the Altoviz MCP Server

Pydantic AI provides unique advantages when paired with Altoviz through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Altoviz integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Altoviz connection logic from agent behavior for testable, maintainable code

Altoviz + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Altoviz MCP Server delivers measurable value.

Type-safe data pipelines: query Altoviz with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Altoviz tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Altoviz and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Altoviz responses and write comprehensive agent tests

Altoviz MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Altoviz to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

Common issues when connecting Altoviz to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Altoviz + Pydantic AI FAQ

Common questions about integrating Altoviz MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Altoviz MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.