How to Use the Measured MCP in LangChain

Q: Can Measured help my LangChain agent optimize budgets?

Yes. The agent uses getincrementalityscores to measure the true impact of each channel. It makes better budget decisions when it has access to Measured data rather than just platform-reported clicks.

Chain Measured marketing data directly into your LangChain agents to automate performance reporting and spend optimization logic.

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Connect Measured MCP to LangChain

Create your Vinkius account to connect Measured 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 Measured with LangChain

Ask AI about this MCP

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Claude

Perplexity

Automate performance pipelines with LangChain

Feed live marketing metrics into your decision chains. By calling `get_performance_summary` as the first step, your agent establishes a baseline for ROAS before triggering downstream logic. Your agent parses the output from `get_campaign_performance` to evaluate specific tactics. It then uses that data as the context for the next link in your execution chain.

Verify channel incrementality in real-time

Connect your agents to `get_incrementality_scores` to ground every budget decision in actual lift data. This prevents your LangChain agents from relying on vanity metrics that don't drive revenue. Instead of guessing, the agent compares `get_performance_by_channel` results against your historical targets. It makes a reasoned choice about whether to scale or cut spend based on the raw numbers.

Trace every marketing data call

Use LangSmith to monitor how your agent interacts with the Measured MCP Server. Every input and output from `list_reports` or `get_insights` is logged for debugging your agent's reasoning process. You see exactly which tool triggered which response. This transparency lets you refine your agent's prompt instructions to improve accuracy when it processes complex marketing reports.

Setup guide

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

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Common questions about Measured MCP in LangChain

You install the MCP adapters and pass the tool list directly to your agent constructor. The agent then dynamically executes the Measured tools as it works through your defined chain.

Yes. The agent uses `get_incrementality_scores` to measure the true impact of each channel. It makes better budget decisions when it has access to Measured data rather than just platform-reported clicks.

Absolutely. Because Measured exposes tools via the standard protocol, your LangChain agents handle the data structures natively. It is a direct integration that requires no custom middleware.

Your agent catches the error through the standard interface. You can build a fallback path in your chain to notify you if a report isn't available.

The server uses a single endpoint token for authentication. Your agent only accesses the specific campaign and integration data you permit through your Measured account settings.

Use it with your favorite AI tools

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

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