How to Use the AdsWizz MCP in LangChain

Q: How do I connect the AdsWizz MCP Server to my LangChain agent?

You'll use the MultiServerMCPClient from the langchain-mcp-adapters package. Point it to your Vinkius endpoint URL. Then, call client.gettools() and pass that list straight into your agent's constructor.

Q: What's the best way to handle multiple MCP Servers in LangChain with AdsWizz?

The MultiServerMCPClient is designed for this. You register the AdsWizz server alongside any others, like a CRM or database server. Your agent gets a single, unified list of tools to work with.

Build LangChain agents that manage your AdsWizz audio campaigns, from performance checks to inventory lists.

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Connect AdsWizz MCP to LangChain

Create your Vinkius account to connect AdsWizz 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 AdsWizz with LangChain

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Chain Campaign Lookups and Performance Checks

Your agent can now run multi-step ad analyses. It starts by calling `list_campaigns` to see what's active, then uses that output to feed `get_audio_performance` for a specific campaign ID. It’s a simple, powerful sequence. This is what LangChain was built for. Your agent isn't just fetching data; it's executing a reasoning process that you design. With LangSmith, you can see the whole chain in action, tracking every tool call to the AdsWizz server and the data that flows between them.

Build Agents that Find Ad Inventory

An agent can find new advertising opportunities on its own. Give it the `list_zones` tool, and it can scout for available podcasts and streams that match your criteria. It can cross-reference those findings with data from `list_campaigns` to avoid placing ads where you already have a presence. You're not just getting a list. You're building a planning agent. This agent can evaluate ad inventory, check it against current campaign goals, and propose a data-backed placement strategy, all within a single chain.

A LangChain MCP Server for Ad Ops

Pulling specific campaign data is now a single tool call. An agent can use `get_campaign` to get the full configuration for any campaign by its ID. This gives the agent the context it needs to answer detailed questions or prepare data for the next step in a chain. This isn't just about retrieving data. It's about making that data an active part of a larger process. Feed the campaign configuration into another tool, combine it with performance metrics, and have your agent generate a complete status report for a stakeholder.

Setup guide

Set up AdsWizz 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 AdsWizz 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({
    "adswizz-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 AdsWizz 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 AdsWizz. 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 AdsWizz MCP in LangChain

You'll use the `MultiServerMCPClient` from the `langchain-mcp-adapters` package. Point it to your Vinkius endpoint URL. Then, call `client.get_tools()` and pass that list straight into your agent's constructor.

Yes, that's a perfect use case for a chain. Your agent would call `get_audio_performance` for each campaign ID, then use its underlying model to compare the metrics. LangSmith will show you the entire trace, step by step.

The `MultiServerMCPClient` is designed for this. You register the AdsWizz server alongside any others, like a CRM or database server. Your agent gets a single, unified list of tools to work with.

Absolutely. That's what LangSmith is for. It provides full observability, showing the exact inputs and outputs for every tool call your LangChain agent makes to the AdsWizz server.

This server only handles your AdsWizz campaign data. That includes performance metrics, campaign details, and ad zone information. Vinkius isolates each request in a sandbox, and your Vinkius token handles authentication so no raw credentials are ever exposed.

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