How to Use the YoneTeam MCP in LangChain

Q: What kind of data does the YoneTeam MCP Server handle regarding suppliers for LangChain?

It manages supplier and offer data. You can call listsuppliers to see approved vendors or use listoffers to get details on specific available offers.

Build complex operational chains with LangChain's multi-step reasoning using the YoneTeam MCP Server.

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…and any MCP-compatible client

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Connect YoneTeam MCP to LangChain

Create your Vinkius account to connect YoneTeam to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup YoneTeam with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequential Operations

The agent calls tools in a specific sequence. Need to find out what supplies you need? First, you call `list_materials_catalog` to see available items. Then, the output feeds directly into calling `create_demand`, which starts the purchasing process.

Order and Supplier Lookup

You can map out your supply chain using chained calls. Check on existing shipments by running `list_purchase_orders`. After getting the PO details, you can run `get_offer_details` to see what suppliers are offering for that item.

Account and Inventory Status

Need a full picture of operations? Start by calling `get_me` to grab your account info. Next, you can use `list_demands` to see all open purchasing requests across the company.

Setup guide

Set up YoneTeam 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 YoneTeam 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({
    "yoneteam-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 YoneTeam transactions"
    })
    print(result["messages"][-1].content)

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Common questions about YoneTeam MCP in LangChain

The MCP Server exposes 10 tools that your agent can use. When you build a chain, the agent decides which tool to call and in what order based on the intermediate results.

Yes, the client supports multi-server aggregation. You can combine MCP tools from different sources into a single reasoning pipeline.

The server exposes purchase order and demand data types. Your agent can read details using `get_order_details` or list general demands with `list_demands`.

It's stateless by default, but you can use client.session() if you need to maintain a consistent context across multiple tool calls in your chain.

It manages supplier and offer data. You can call `list_suppliers` to see approved vendors or use `list_offers` to get details on specific available offers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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