Netease Yunxin / 网易云信 MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Netease Yunxin / 网易云信 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({
"netease-yunxin": {
"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 Netease Yunxin / 网易云信, 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 Netease Yunxin / 网易云信 MCP Server
Empower your AI agent to orchestrate your real-time communication infrastructure with Netease Yunxin (网易云信), the premier provider of IM and RTC services in China. By connecting Yunxin to your agent, you transform complex user account management, group/team orchestration, and historical message auditing into a natural conversation. Your agent can instantly create IM accounts, manage chat group memberships, send direct or batch messages, and browse historical sessions without you ever needing to navigate a technical dashboard. Whether you are building an automated community management system or auditing customer interactions, your agent acts as a real-time communication assistant, providing reliable and secure results from a single, unified source.
LangChain's ecosystem of 500+ components combines seamlessly with Netease Yunxin / 网易云信 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
- Account Orchestration — Create, update, and refresh tokens for IM users with full support for unique accids.
- Messaging Control — Send direct P2P messages or high-volume batch messages between your user accounts.
- Group/Team Management — Create multi-user teams, add or kick members, and audit team configuration details.
- History Auditing — Retrieve and browse historical messages between users within specific time ranges.
- System Monitoring — Coordinate service status and monitor IM connectivity across your entire application.
The Netease Yunxin / 网易云信 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 Netease Yunxin / 网易云信 to LangChain via MCP
Follow these steps to integrate the Netease Yunxin / 网易云信 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 Netease Yunxin / 网易云信 via MCP
Why Use LangChain with the Netease Yunxin / 网易云信 MCP Server
LangChain provides unique advantages when paired with Netease Yunxin / 网易云信 through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Netease Yunxin / 网易云信 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 Netease Yunxin / 网易云信 queries for multi-turn workflows
Netease Yunxin / 网易云信 + LangChain Use Cases
Practical scenarios where LangChain combined with the Netease Yunxin / 网易云信 MCP Server delivers measurable value.
RAG with live data: combine Netease Yunxin / 网易云信 tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Netease Yunxin / 网易云信, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Netease Yunxin / 网易云信 tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Netease Yunxin / 网易云信 tool call, measure latency, and optimize your agent's performance
Netease Yunxin / 网易云信 MCP Tools for LangChain (10)
These 10 tools become available when you connect Netease Yunxin / 网易云信 to LangChain via MCP:
add_team_member
Add members to team
create_account
Create IM account
create_team
Create chat group/team
get_session_history
Get chat history
get_team_detail
Get team details
kick_team_member
Remove member from team
refresh_user_token
Refresh user IM token
send_batch_message
Send batch messages
send_p2p_message
Send P2P message
update_account
Update IM account
Example Prompts for Netease Yunxin / 网易云信 in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Netease Yunxin / 网易云信 immediately.
"Create a new IM account with accid 'user_8821'."
"Send a message from 'admin' to 'user_8821' saying 'Welcome to the platform!'."
"Create a chat team 'Project Alpha' with owner 'admin' and members 'user_01,user_02'."
Troubleshooting Netease Yunxin / 网易云信 MCP Server with LangChain
Common issues when connecting Netease Yunxin / 网易云信 to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersNetease Yunxin / 网易云信 + LangChain FAQ
Common questions about integrating Netease Yunxin / 网易云信 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 Netease Yunxin / 网易云信 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 Netease Yunxin / 网易云信 to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.