GeTui / 个推 MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect GeTui / 个推 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"getui": {
"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 GeTui / 个推, 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 GeTui / 个推 MCP Server
Empower your AI agent to orchestrate your push notification infrastructure with GeTui (个推), the dominant CPaaS and developer services provider in China. By connecting GeTui to your agent, you transform complex device targeting, message broadcasting, and delivery auditing into a natural conversation. Your agent can instantly send targeted notifications to specific users, broadcast messages to your entire user base, retrieve real-time delivery and click statistics, and monitor user online status without you ever needing to navigate the comprehensive GeTui Developer Center. Whether you are automating verification flows or coordinating large-scale promotional alerts, your agent acts as a real-time messaging assistant, keeping your communication flow accurate and your user insights up-to-date.
LangChain's ecosystem of 500+ components combines seamlessly with GeTui / 个推 through native MCP adapters. Connect 10 tools via 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
- Push Orchestration — Send targeted, list-based, or broadcast notifications with full support for custom payloads.
- User Status Monitoring — Retrieve real-time online/offline status and associate custom aliases with Client IDs (CIDs).
- Tag & Interest Auditing — Browse user tags to identify audience segments and interest patterns for refined targeting.
- Delivery Analytics — Access real-time statistics for push tasks, including delivery counts, display rates, and clicks.
- Growth Insights — Monitor application-wide statistics for new and active users across specific dates.
The GeTui / 个推 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 GeTui / 个推 to LangChain via MCP
Follow these steps to integrate the GeTui / 个推 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 GeTui / 个推 via MCP
Why Use LangChain with the GeTui / 个推 MCP Server
LangChain provides unique advantages when paired with GeTui / 个推 through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine GeTui / 个推 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 GeTui / 个推 queries for multi-turn workflows
GeTui / 个推 + LangChain Use Cases
Practical scenarios where LangChain combined with the GeTui / 个推 MCP Server delivers measurable value.
RAG with live data: combine GeTui / 个推 tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query GeTui / 个推, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain GeTui / 个推 tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every GeTui / 个推 tool call, measure latency, and optimize your agent's performance
GeTui / 个推 MCP Tools for LangChain (10)
These 10 tools become available when you connect GeTui / 个推 to LangChain via MCP:
bind_user_alias
g., username) with a Client ID. Bind alias to user
get_app_user_stats
Get application user stats
get_cid_status
Check user online status
get_daily_push_report
Get daily push report
get_push_status
Check push task status
get_user_tags
Get user tags
push_to_all
Broadcast push to all users
push_to_list
Send push to multiple users
push_to_single
Send push to single user
query_user_alias
Query user alias
Example Prompts for GeTui / 个推 in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with GeTui / 个推 immediately.
"Send a push notification to CID '1a0918c...' with title 'Urgent Update'."
"Check the online status for user CID '9920a1b...'."
"Show me the push report for yesterday."
Troubleshooting GeTui / 个推 MCP Server with LangChain
Common issues when connecting GeTui / 个推 to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGeTui / 个推 + LangChain FAQ
Common questions about integrating GeTui / 个推 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 GeTui / 个推 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 GeTui / 个推 to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.