How to Use the Mux MCP in LangChain

Build automated video pipelines directly in LangChain using Mux.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Mux MCP to LangChain

Create your Vinkius account to connect Mux 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.

GDPR Free for Subscribers

Setup Mux with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Mux MCP Server Operations

Calling `create_asset` via the Mux MCP Server gives your LangChain agent direct control over video ingest. You drop the tool into a ReAct agent, and it handles the entire upload process without you writing custom API wrappers. Your agent pulls an upload URL via `create_direct_upload` to feed the next step in your chain. It passes the link to an external storage node, then verifies the video state with `get_asset`. Every step gets logged in LangSmith so you can track exact token usage.

Spin Up Live Broadcasts

Your agent executes `create_live_stream` to generate a secure stream key and playback ID on the fly. Triggering a live broadcast requires zero dashboard clicking. The agent runs `delete_live_stream` to kill the ingest endpoint when the event ends. This prevents unauthorized broadcasts and keeps your billing predictable. You build the logic once, and the machine executes the sequence perfectly.

Track Video Performance

Executing `get_recent_views` pulls raw playback metrics straight into your LangChain pipeline. Agents need these feedback loops to make decisions about content. The agent scans your library with `list_assets` the moment a video flatlines. It cross-references the view counts and automatically purges dead weight using `delete_asset`.

Setup guide

Set up Mux 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 Mux 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({
    "mux-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 Mux transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mux. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Mux now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Mux MCP in LangChain

Install the adapters package and define a multi-server client. Pass your endpoint URL to the transport config, fetch the tools, and hand them directly to your agent.

Yes. LangSmith automatically traces every MCP execution. You see exactly how long the server took to resolve and the exact payload returned.

Your agent reads the initial response. If it hits a limit, you configure the ReAct loop to request the next batch until it finds the target video.

That is the whole point. You pull video metrics, format them, and pipe the data into a reporting tool using a different integration.

The MCP server executes locally within your environment. Vinkius manages the connection tunnel but never inspects or stores the payloads.

Use it with your favorite AI tools

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