How to Use the Microsoft Ads MCP in LangChain

Q: How do I register the Microsoft Ads MCP Server with LangChain?

Install the adapter using pip install langchain-mcp-adapters langgraph. Then, initialize the MultiServerMCPClient with the server URL and pass the tools directly to your agent constructor.

Q: Can my LangChain agent analyze keyword performance using Microsoft Ads?

Yes, your agent can call listmskeywords to pull keywords for specific ad groups. It can then chain this data with other LangChain tools to evaluate search intent.

Q: Can I search for specific campaigns using this integration?

Yes, the server includes searchmscampaigns which lets your agent locate campaigns by name. This is ideal for targeted reporting tasks.

Q: How is my Microsoft Ads campaign budget data secured?

Your budget data accessed via listmsbudgets is processed in a secure V8 isolate sandbox using the MCP protocol. Vinkius ensures that credentials never touch the LangChain client or any external storage.

Get Microsoft Ads performance data directly into your LangChain multi-step reasoning chains.

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Connect Microsoft Ads MCP to LangChain

Create your Vinkius account to connect Microsoft 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 Microsoft Ads with LangChain

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Chain Microsoft Ads discovery into your LangChain runs

The `list_ms_campaigns` tool, running on our MCP Server, lets your LangChain agent fetch active campaigns to kick off complex multi-step reasoning chains. Your agent runs this output directly into `list_ms_ad_groups` to map your entire account structure in a single run. This setup feeds live campaign data straight into your LangSmith traces. You see the exact inputs and outputs of `get_ms_campaign_details` inside your run history without guessing why a decision was made.

Map ad group details with LangChain ReAct loops

The `get_ms_ad_group_details` tool provides the critical structural data your ReAct agents need to evaluate performance. By exposing this tool to your LangGraph agent, the model decides when to inspect specific groups based on real-time campaign performance. Your agent executes a loop, using `list_ms_ads` to check creative copy and then pulling `list_ms_keywords` to analyze search query alignment. The LangChain adapter passes these parameters directly, letting the agent build a complete contextual picture of your ad groups.

Track Microsoft Ads budgets inside LangSmith

This MCP tool, specifically `list_ms_budgets`, exposes shared budgets to your LangChain pipeline so you can monitor spend limits dynamically. Your chain pulls current budget allocations and matches them against active campaign metrics in a single execution block. By tracking these tool calls in LangSmith, you monitor latency and token costs for every budget check. This keeps your automated ad monitoring fast and prevents runaway API spend.

Setup guide

Set up Microsoft 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 Microsoft 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({
    "microsoft-ads-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 Microsoft 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 Microsoft 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 Microsoft Ads MCP in LangChain

Install the adapter using `pip install langchain-mcp-adapters langgraph`. Then, initialize the `MultiServerMCPClient` with the server URL and pass the tools directly to your agent constructor.

Yes, your agent can call `list_ms_keywords` to pull keywords for specific ad groups. It can then chain this data with other LangChain tools to evaluate search intent.

LangChain executes the tools synchronously or asynchronously within your defined chains. You should implement rate-limiting wrappers around your `MultiServerMCPClient` calls to prevent hitting Microsoft's API thresholds.

Yes, the server includes `search_ms_campaigns` which lets your agent locate campaigns by name. This is ideal for targeted reporting tasks.

Your budget data accessed via `list_ms_budgets` is processed in a secure V8 isolate sandbox using the MCP protocol. Vinkius ensures that credentials never touch the LangChain client or any external storage.

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