Can I use this to generate a formula for a new plant-based meat?

Yes! Use the `create_formulation` tool to instruct Giuseppe to model a specific animal product (e.g., 'Target: Pulled Pork'). You can pass constraints like 'no soy' or 'must contain pea protein'. Giuseppe will return a mathematically generated formula combining plant extracts that mimic the target's molecular profile.

How does Giuseppe match specific flavors?

The `search_flavor_matches` tool analyzes NotCo's proprietary database. Instead of searching for 'beef flavor', Giuseppe searches for the specific volatile molecular compounds that create the beef flavor, and then finds combinations of seemingly unrelated plants (like pineapple and cabbage) that, when combined mathematically, replicate that exact molecular behavior.

Can I predict the cost of a new formulation before making it?

Absolutely. Once Giuseppe generates a formulation, you can pass its ID to the `estimate_cost` tool. The API cross-references the required plant ingredients with global B2B commodity pricing databases to give you an estimated per-kilogram cost for mass production.

NotCo MCP Server for LlamaIndex 14 tools — connect in under 2 minutes

Name: NotCo
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 14 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NotCo as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 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 NotCo. "
            "You have 14 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in NotCo?"
    )
    print(response)

asyncio.run(main())

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About NotCo MCP Server

Connect your AI agent directly to Giuseppe, NotCo’s proprietary Food Tech AI platform. Accelerate your B2B food research and development by commanding Giuseppe through natural language.

LlamaIndex agents combine NotCo tool responses with indexed documents for comprehensive, grounded answers. Connect 14 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

AI Formulation Generation — Command Giuseppe to analyze the molecular structure of an animal product and generate a plant-based blueprint using combinations from a database of over 300,000 plants
Ingredient Search — Browse and retrieve the molecular, sensory, and functional profiles of thousands of plant extracts and proteins
Flavor & Texture Matching — Use AI computational models to find plant compounds that replicate specific volatile molecules, aromas, and mouthfeels
Nutritional Label Prediction — Run predictive algorithms on custom plant mixtures to estimate the final nutritional values of a recipe before entering the lab
Cost Estimation — Predict the theoretical mass-production cost of an AI-generated formula based on global commodity pricing

The NotCo MCP Server exposes 14 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 NotCo to LlamaIndex via MCP

Follow these steps to integrate the NotCo 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 14 tools from NotCo

Why Use LlamaIndex with the NotCo MCP Server

LlamaIndex provides unique advantages when paired with NotCo through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine NotCo tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain NotCo tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query NotCo, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what NotCo tools were called, what data was returned, and how it influenced the final answer

NotCo + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the NotCo MCP Server delivers measurable value.

Hybrid search: combine NotCo real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query NotCo 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 NotCo for fresh data

Analytical workflows: chain NotCo queries with LlamaIndex's data connectors to build multi-source analytical reports

NotCo MCP Tools for LlamaIndex (14)

These 14 tools become available when you connect NotCo to LlamaIndex via MCP:

analyze_nutrition

Analyze the nutritional output of a formulation

create_formulation

Request a new AI formulation

create_project

Create a new R&D project

estimate_cost

Predict the mass production cost of a formulation

get_formulation

Get details of a specific AI formulation

get_ingredient

Get complete molecular profile of an ingredient

list_formulations

g., dairy, meat, sauces). List plant-based AI formulations

list_ingredients

Search the plant-based ingredient molecular database

list_nutritional_profiles

List target nutritional benchmarks

list_projects

List active R&D projects

list_sensory_profiles

List standard sensory profiles

list_suppliers

List approved ingredient suppliers

run_sensory_test

Run an AI simulation of a sensory test

search_flavor_matches

Find plant combinations that mimic a target flavor

Example Prompts for NotCo in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with NotCo immediately.

"Ask Giuseppe to create a plant-based alternative for condensed milk, with the constraint 'no palm oil'."

"Run a nutritional analysis on formulation ID #CM-882."

"Estimate the mass-production cost for this formulation."

Troubleshooting NotCo MCP Server with LlamaIndex

Common issues when connecting NotCo to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

NotCo + LlamaIndex FAQ

Common questions about integrating NotCo MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.