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 LangChain 10 tools — connect in under 2 minutes

Name: InnoVint
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect InnoVint through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "innovint": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using InnoVint, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

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.

LangChain's ecosystem of 500+ components combines seamlessly with InnoVint through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the InnoVint MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from InnoVint via MCP

Why Use LangChain with the InnoVint MCP Server

LangChain provides unique advantages when paired with InnoVint through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine InnoVint MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across InnoVint queries for multi-turn workflows

InnoVint + LangChain Use Cases

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

RAG with live data: combine InnoVint tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query InnoVint, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain InnoVint tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every InnoVint tool call, measure latency, and optimize your agent's performance

InnoVint MCP Tools for LangChain (10)

These 10 tools become available when you connect InnoVint to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

InnoVint + LangChain FAQ

Common questions about integrating InnoVint MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.