InnoVint 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 InnoVint 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 InnoVint. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in InnoVint?"
)
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 InnoVint MCP Server
Connect your InnoVint winery to any AI agent and transform how your cellar team works — from harvest intake to bottling.
LlamaIndex agents combine InnoVint 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
- 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 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 InnoVint to LlamaIndex via MCP
Follow these steps to integrate the InnoVint 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 InnoVint
Why Use LlamaIndex with the InnoVint MCP Server
LlamaIndex provides unique advantages when paired with InnoVint through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine InnoVint tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain InnoVint tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query InnoVint, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what InnoVint tools were called, what data was returned, and how it influenced the final answer
InnoVint + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the InnoVint MCP Server delivers measurable value.
Hybrid search: combine InnoVint real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query InnoVint 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 InnoVint for fresh data
Analytical workflows: chain InnoVint queries with LlamaIndex's data connectors to build multi-source analytical reports
InnoVint MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect InnoVint to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting InnoVint to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpInnoVint + LlamaIndex FAQ
Common questions about integrating InnoVint 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 InnoVint 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 InnoVint to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.