How to Use the Ingredient Weight Converter MCP in LangChain

Build precise, chainable culinary logic in LangChain by converting volumes to exact gram weights using the Ingredient Weight Converter.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Ingredient Weight Converter MCP to LangChain

Create your Vinkius account to connect Ingredient Weight Converter to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Ingredient Weight Converter with LangChain

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ChatGPT

Claude

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Gemini

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Chainable weight calculations

Stop guessing at cup sizes. Use `convert_volume_to_weight` to feed precise gram values directly into your next processing step. Your agent handles the math. It turns raw volume data into consistent mass measurements for your chains.

Dynamic ingredient lookups

Access specific density data for any item. Use `get_ingredient_density` to pull the exact weight per cup before the agent starts its calculation. This ensures your chain isn't working off outdated assumptions. It brings real-world kitchen data into your pipeline.

Automated pantry searches

Find the right item without manual browsing. Use `search_ingredients` to locate your target within the database before running conversions. This makes your MCP integration more reliable. It prevents errors by confirming the ingredient identity before the logic executes.

Setup guide

Set up Ingredient Weight Converter MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Ingredient Weight Converter tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "ingredient-weight-converter-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Ingredient Weight Converter transactions"
    })
    print(result["messages"][-1].content)

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