How do I get InnoVint API access?

Contact InnoVint support at support@innovint.us to request a Personal Access Token. You'll need an active InnoVint account.

Can I record lab analysis results using this integration?

Yes, you can input new lab readings such as pH, TA, Brix, and free SO2 directly for a specific lot or vessel using natural language, and the AI will post them to the InnoVint API.

Does this support managing multiple wineries under the same account?

Yes, if your InnoVint integrator account has access to multiple wineries, you can scope your API requests to a specific Winery ID to manage lots and vessels across different properties.

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

Name: InnoVint
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 InnoVint through the 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 InnoVint "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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About InnoVint MCP Server

Connect your InnoVint winery to any AI agent and transform how your cellar team works — from harvest intake to bottling.

Pydantic AI validates every InnoVint tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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

Lots — Search and track wine lots by varietal, vintage, lot code, or vessel assignment
Vessels — Monitor tanks, barrels, concrete eggs, and amphorae — capacity, fill level, and contents
Lab Analyses — View pH, TA, SO2, Brix, RS, VA, and alcohol readings for any lot over time
Cellar Actions — Track rackings, pump-overs, punchdowns, additions, fining, and filtration history
Wines & Vintages — Browse wine products and navigate production by vintage year
Additives — Reference registered chemicals, enzymes, and fining agents with dosage guidelines
Multi-Winery — Manage multiple wineries from a single AI connection

The InnoVint 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 InnoVint to Pydantic AI via MCP

Follow these steps to integrate the InnoVint 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 InnoVint with type-safe schemas

Why Use Pydantic AI with the InnoVint MCP Server

Pydantic AI provides unique advantages when paired with InnoVint 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 InnoVint integration code

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

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

InnoVint + Pydantic AI Use Cases

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

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

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

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

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

InnoVint MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect InnoVint to Pydantic AI via MCP:

get_lot

The primary data point for any winemaking question. Get full lot details

get_vessel

Essential for barrel program management. Get vessel details

list_actions

Filter by lot to see complete cellar history. List cellar actions

list_additives

With regulatory limits and typical dosage. List additives

list_analyses

Filter by lot to see a specific wine's chemistry over time. List lab analyses

list_vessels

Shows capacity, current contents, fill level, and location. Critical for cellar management and space planning. List tanks and barrels

list_vintages

Navigate wine production by year. List vintages

list_wineries

Multi-winery operations can manage several facilities from one account. List wineries

list_wines

Each with varietal rules, appellation, and production notes. List wine products

search_lots

Returns lot details including volume, vessel assignment, varietal composition, and current status. Essential for tracking individual batches through the winemaking process — from harvest intake to bottling. Search wine lots

Example Prompts for InnoVint in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with InnoVint immediately.

"How is the 2025 Pinot Noir fermentation going?"

"Record a new lab reading for the 2025 Chardonnay: pH is 3.32 and TA is 6.5 g/L."

"Which vessels are currently empty and available for the upcoming harvest?"

Troubleshooting InnoVint MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

InnoVint + Pydantic AI FAQ

Common questions about integrating InnoVint 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 InnoVint MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.