How to Use the Videco MCP in LangChain

Q: How do I use Videco and LangChain together for lead tracking?

Your agent first calls listleads via the MCP Server. This gives you a full list of contacts. Then, it can use that data to determine which campaigns need updates before calling getcampaign.

Q: What kind of video analytics does Videco provide with LangChain?

The MCP Server allows your agent to call getvideoanalytics. This pulls specific performance data on videos, letting you know which content is working and where leads are dropping off.

Q: Can I list all campaigns using Videco with LangChain?

Absolutely. You can use the listcampaigns tool right from your chain. This lets you get a full overview of every campaign you've run or plan to run through the MCP Server.

Q: If I change my mind, how do I check Videco status with LangChain?

You can always verify connectivity first. The checkvidecostatus tool lets your agent confirm that the entire Videco API is up and running before it attempts to create any content or read leads.

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Create your Vinkius account to connect Videco 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 Videco with LangChain

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Orchestrate Video Campaigns via MCP Server

You can chain together multiple actions to manage your entire video lifecycle. Start by listing all campaigns (`list_campaigns`) and then check the status of a specific one using `get_campaign`. This workflow lets you build multi-step logic where checking data feeds into creating new content or targeting leads.

Track Leads and Video Performance

Need to know who's watching and who needs follow-up? First, get a list of all captured leads (`list_leads`). Next, you can use `get_video_analytics` to pull performance metrics for videos. Running these two steps together lets your agent identify high-value leads based on engagement data.

Manage Full Video Assets

Dealing with personalized video assets? You'll use `list_videos` to see what you have, and then grab specific details using `get_video`. If you need to make a fresh asset, the agent calls `create_video`, ensuring that every step—from listing to creation—is visible in your LangChain chain.

Setup guide

Set up Videco 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 Videco 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({
    "videco-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 Videco 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 Videco. 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 Videco MCP in LangChain

Your agent first calls `list_leads` via the MCP Server. This gives you a full list of contacts. Then, it can use that data to determine which campaigns need updates before calling `get_campaign`.

The MCP Server allows your agent to call `get_video_analytics`. This pulls specific performance data on videos, letting you know which content is working and where leads are dropping off.

Absolutely. You can use the `list_campaigns` tool right from your chain. This lets you get a full overview of every campaign you've run or plan to run through the MCP Server.

You can always verify connectivity first. The `check_videco_status` tool lets your agent confirm that the entire Videco API is up and running before it attempts to create any content or read leads.

This server handles lead details. Specifically, you can retrieve full customer records by calling the `get_lead` tool. Remember that all PII is managed through these explicit API calls.

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