How to Use the GeTui / 个推 MCP in LangChain

Q: How do I connect GeTui / 个推 to my LangChain agents?

Install langchain-mcp-adapters and langgraph. Pass your GeTui credentials into a MultiServerMCPClient configuration. Call client.gettools() and hand the array to your ReAct agent.

Q: How do I handle offline devices in my LangGraph workflow?

Add a conditional node that runs getcidstatus. If the device is offline, route the workflow to an email fallback instead of calling the push tools.

Build multi-step push notification pipelines in LangChain using this MCP Server.

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Connect GeTui / 个推 MCP to LangChain

Create your Vinkius account to connect GeTui / 个推 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 GeTui / 个推 with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Dynamic audience targeting

`get_user_tags` and `get_cid_status` let your LangChain agents verify device readiness before sending anything. The agent queries the metadata. It checks if the client ID is currently online. Then it decides to execute an immediate alert or hold off until peak hours. You chain these tools directly into `push_to_single`. The output from the status check becomes the exact input for the push command. LangSmith traces the entire pipeline, so you see the API latency and the exact JSON payload that triggered the notification.

Bulk campaign execution via MCP Server

`push_to_list` and `push_to_all` give your ReAct agents the ability to run massive marketing broadcasts. The agent compiles an audience list from your database, formats the CIDs, and fires them into the GeTui MCP Server. We bypass manual dashboard work entirely. If a campaign requires alias mapping, the agent calls `bind_user_alias` first to link your internal user IDs with GeTui's system. The chain handles the data transformation automatically.

Automated reporting loops

`get_daily_push_report` and `get_app_user_stats` pull raw campaign metrics back into your reasoning loop. Your agent grabs yesterday's open rates and click-through data to determine if the next message needs a different subject line. Tracking individual messages happens through `get_push_status`. The agent pulls the task ID from a previous push operation and checks if the delivery actually succeeded. It then logs that final state into your analytics database.

Setup guide

Set up GeTui / 个推 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 GeTui / 个推 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({
    "getui-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 GeTui / 个推 transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GeTui / 个推. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about GeTui / 个推 MCP in LangChain

Install `langchain-mcp-adapters` and `langgraph`. Pass your GeTui credentials into a `MultiServerMCPClient` configuration. Call `client.get_tools()` and hand the array to your ReAct agent.

Yes. The agent stores the task ID after sending a message. It then runs `get_push_status` to verify delivery.

Every tool execution logs directly to LangSmith. You see the exact JSON payload sent to GeTui and the response latency. This makes debugging failed pushes much easier.

Add a conditional node that runs `get_cid_status`. If the device is offline, route the workflow to an email fallback instead of calling the push tools.

Vinkius runs this MCP integration inside an ephemeral V8 Isolate. The server handles Client IDs (CIDs) and user tags, but it drops all memory the millisecond the request finishes. Your API tokens stay locked in the sandbox environment.

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