How to Use the 4YouSee MCP in LangChain

Q: Can LangChain trace 4YouSee tool calls?

Yes. Every call to getplayer or listmedias shows up in LangSmith. You see the exact latency and token usage for each signage query.

Q: Does 4YouSee work with LangGraph?

It works natively. You map specific tools like listtemplates to individual nodes in your graph architecture.

Build multi-step digital signage workflows by connecting 4YouSee to LangChain.

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Connect 4YouSee MCP to LangChain

Create your Vinkius account to connect 4YouSee 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 4YouSee with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

LangChain ReAct agents for player states

Your LangChain agent calls `list_players` to find offline screens across your network. It pipes those raw IDs directly into `get_player` to pull the exact hardware error state. The ReAct framework decides what to check next based on that output. You get full visibility into the execution path through LangSmith traces, seeing exactly how long the signage query took.

Audit signage networks with MCP Servers

Build a chain that grabs active content using `list_medias` and compares it against expected layouts from `list_templates`. The MCP Server handles the raw data extraction from your platform. Output from the 4YouSee tools feeds right into your LLM node for analysis. You spot missing video assets before they ever hit the physical displays.

Map platform access dynamically

Pass the `list_users` tool to a LangGraph node to pull your entire permission structure. The agent maps out exactly who controls which display group. Combine this with external directory APIs in the same chain. You write custom logic to alert administrators when orphaned accounts still have publishing rights on your screens.

Setup guide

Set up 4YouSee 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 4YouSee 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({
    "4yousee-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 4YouSee 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 4YouSee. 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.

Why Choose Vinkius

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Common questions about 4YouSee MCP in LangChain

Use MultiServerMCPClient pointing to your Vinkius endpoint URL. Call client.get_tools() and pass the resulting array to your agent executor.

Yes. Every call to get_player or list_medias shows up in LangSmith. You see the exact latency and token usage for each signage query.

It works natively. You map specific tools like list_templates to individual nodes in your graph architecture.

The LLM reads the tool schemas provided by the server. It knows to run list_players first to grab the required ID before fetching details.

Vinkius runs the integration inside an ephemeral V8 Isolate sandbox. Your player monitoring logs and user lists never touch persistent storage. The connection drops the moment the chain finishes executing.

Use it with your favorite AI tools

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

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