How to Use the LinkedIn Ads MCP in LangChain

Q: How do I connect LinkedIn Ads to my LangChain agent?

Install langchain-mcp-adapters and use MultiServerMCPClient pointing to the Vinkius endpoint. Retrieve the tools using client.gettools() and pass them directly to your createagent call.

Q: Can LangChain automate budget optimization on LinkedIn Ads?

Yes. Your agent can poll metrics using getcampaignanalytics and execute bid adjustments or pause campaigns using pausecampaign based on rules you define in your chain.

Pipe real-time B2B performance metrics directly into your LangChain decision chains to pause underperforming campaigns instantly.

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Connect LinkedIn Ads MCP to LangChain

Create your Vinkius account to connect LinkedIn Ads 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 LinkedIn Ads with LangChain

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Control budgets with LangChain and this MCP Server

The `pause_campaign` tool stops active LinkedIn campaigns when performance drops below your target threshold. Your LangChain agent evaluates live cost-per-acquisition metrics against your budget limits and makes the call to pause or resume. Using `enable_campaign` alongside this, the chain reacts to performance spikes by turning on high-value campaign groups. You build a closed-loop system where the agent acts as your media buyer, running continuously without human lag.

Multi-step B2B performance audits

The `get_campaign_analytics` tool fetches raw performance metrics for individual campaigns over specified time windows. LangChain passes these raw numbers directly into downstream analysis steps, feeding them into vector databases or summarizing them for executive reports. By chaining this with `list_creatives`, the agent maps specific creative assets to high-performing campaigns. This lets your pipeline identify which copy or image drives the lowest cost per lead without manual matching.

Map account structure programmatically

The `list_campaign_groups` tool retrieves the entire structure of your LinkedIn advertising account. Your agent uses this structural map to navigate complex account setups and locate specific target audiences or active initiatives. Combine this with `get_account_info` and `list_campaigns` to build an automated onboarding chain for new clients. The LangChain framework handles the sequential execution, passing account IDs from one step to the next to build a complete visual report.

Setup guide

Set up LinkedIn Ads 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 LinkedIn Ads 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({
    "linkedin-ads-1-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 LinkedIn Ads 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 LinkedIn Ads. 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 LinkedIn Ads MCP in LangChain

Install `langchain-mcp-adapters` and use `MultiServerMCPClient` pointing to the Vinkius endpoint. Retrieve the tools using `client.get_tools()` and pass them directly to your `create_agent` call.

Yes. Your agent can poll metrics using `get_campaign_analytics` and execute bid adjustments or pause campaigns using `pause_campaign` based on rules you define in your chain.

LangSmith traces the exact inputs and outputs of tools like `list_campaigns` and `get_account_analytics`. You see exactly why your agent decided to pause a campaign or what payload it received.

This MCP Server translates complex LinkedIn Ads API schemas into clean tools your agent understands out of the box. You avoid writing boilerplate integration code and handling custom authentication flows.

Your ad account metadata, campaign structures, and performance analytics never persist on Vinkius. The platform executes calls inside isolated V8 sandboxes, acting as a secure, ephemeral bridge between LangChain and LinkedIn via our managed MCP infrastructure.

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