Yonyou / 用友 MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Yonyou / 用友 through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"yonyou": {
"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 Yonyou / 用友, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Yonyou / 用友 MCP Server
Empower your AI agent to orchestrate your entire enterprise operations with Yonyou (用友), the dominant ERP and cloud services provider in China. By connecting Yonyou to your agent, you transform complex business management, supply chain tracking, and financial auditing into a natural conversation. Your agent can instantly list purchase and sales orders, retrieve detailed material metadata, monitor inventory levels, and even browse financial vouchers without you ever needing to navigate the comprehensive YonBIP interface. Whether you are conducting a procurement audit or monitoring sales performance across multiple regions, your agent acts as a real-time operations assistant, keeping your ERP data accurate and your business moving.
LangChain's ecosystem of 500+ components combines seamlessly with Yonyou / 用友 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
- Supply Chain Orchestration — List and retrieve detailed information about purchase and sales orders.
- Master Data Control — Browse materials, customers, and suppliers to identify key business entities.
- Inventory Monitoring — Query real-time inventory levels for items across different warehouses.
- Financial Auditing — Browse accounting vouchers and retrieve high-level organizational metadata.
- Operational Insights — Retrieve high-level summaries of organization-wide business activity and performance.
The Yonyou / 用友 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 Yonyou / 用友 to LangChain via MCP
Follow these steps to integrate the Yonyou / 用友 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 Yonyou / 用友 via MCP
Why Use LangChain with the Yonyou / 用友 MCP Server
LangChain provides unique advantages when paired with Yonyou / 用友 through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Yonyou / 用友 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 Yonyou / 用友 queries for multi-turn workflows
Yonyou / 用友 + LangChain Use Cases
Practical scenarios where LangChain combined with the Yonyou / 用友 MCP Server delivers measurable value.
RAG with live data: combine Yonyou / 用友 tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Yonyou / 用友, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Yonyou / 用友 tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Yonyou / 用友 tool call, measure latency, and optimize your agent's performance
Yonyou / 用友 MCP Tools for LangChain (10)
These 10 tools become available when you connect Yonyou / 用友 to LangChain via MCP:
get_inventory
Query ERP inventory
get_org_info
Get organization metadata
get_purchase_order
Get purchase order details
get_sales_order
Get sales order details
list_customers
List ERP customers
list_materials
List master data materials
list_purchase_orders
List ERP purchase orders
list_sales_orders
List ERP sales orders
list_suppliers
List ERP suppliers
list_vouchers
List financial vouchers
Example Prompts for Yonyou / 用友 in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Yonyou / 用友 immediately.
"List the last 5 purchase orders in Yonyou."
"What is the current inventory for material ID 'MAT-8821'?"
"Show me the organization structure defined in our ERP."
Troubleshooting Yonyou / 用友 MCP Server with LangChain
Common issues when connecting Yonyou / 用友 to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersYonyou / 用友 + LangChain FAQ
Common questions about integrating Yonyou / 用友 MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Yonyou / 用友 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 Yonyou / 用友 to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
